CN113165676B - Inspection system, inspection method, and storage medium - Google Patents

Abstract

The invention relates to an inspection system, an inspection method, and a program. The inspection device (500) derives a state variable by applying a measured value of the front-rear force and an actual value of the conversion variable to the Kalman filter. At this time, a predetermined constant value (for example, 0 (zero)) is used as a value (acceleration in the left-right direction of the vehicle body (11), the trucks (12 a, 12 b), and the axles (13 a to 13 d)) which is originally given as a measurement value of an observation variable at the time of data assimilation.

Description

Inspection system, inspection method, and storage medium

Technical Field

The present invention relates to an inspection system, an inspection method, and a storage medium, and can be used particularly favorably for inspecting a rail of a railway vehicle. The present application is based on Japanese patent application No. 2018-230834 filed on 10/12/2018 and claims priority, the contents of which are incorporated herein in their entirety.

Background

When a railway vehicle runs on a track, the position of the track changes due to the load from the railway vehicle. When such a change in track occurs, the railway vehicle may exhibit abnormal behavior. Accordingly, patent document 1 discloses the following technique: the angular displacement in the yaw direction of the wheel axle, the state variable obtained by the filter for data assimilation, and the measured value of the front-rear force, which is the front-rear force generated in the member for supporting the axle box, are substituted into the motion equation describing the yaw of the wheel axle, and the track irregularity (the through-end irregularity, etc.) of the railway vehicle is derived.

Prior art literature

Patent literature

Patent document 1: international publication No. 2017/164133

Disclosure of Invention

Problems to be solved by the invention

However, in the technique described in patent document 1, in data assimilation, measurement values of forces in the front-rear direction, measurement values of accelerations in the left-right direction of the wheel axle and the bogie (including the vehicle body as required), respectively, are used. These measurement values can be obtained without using a special sensor, but the number of sensors to be disposed in the railway vehicle is preferably small.

The present invention has been made in view of the above-described problems, and an object of the present invention is to reduce the number of sensors used for detecting irregularities in a rail of a railway vehicle.

Means for solving the problems

The inspection system of the present invention is characterized by comprising: a data acquisition unit that acquires data of a measurement value of a force in the front-rear direction as data of a measurement value measured by running a railway vehicle having a vehicle body, a bogie, and an axle on a track; a state variable deriving unit that derives a state variable to be determined in a state equation configured by using a motion equation describing the motion of the railway vehicle, using the measured value of the front-rear force; and a track state deriving unit that derives information reflecting a state of the track, the forward-backward force being a force in a forward-backward direction generated in a member disposed between the wheel axle and the bogie provided with the wheel axle and being a force determined based on a difference between an angular displacement in a yaw direction of the wheel axle and an angular displacement in a yaw direction of the bogie provided with the wheel axle, the member being a member for supporting an axle box, the forward-backward direction being a direction along a traveling direction of the railway vehicle, the yaw direction being a rotational direction with a vertical direction perpendicular to the track as a rotational axis, the state equation being an equation described using the state variable, the forward-backward force, and a conversion variable, the state variables include a displacement and a velocity in a left-right direction of the bogie, an angular displacement and an angular velocity in a yaw direction of the bogie, an angular displacement and an angular velocity in a roll direction of the bogie, a displacement and a velocity in a left-right direction of the wheel axle, and an angular displacement in a roll direction of an air spring attached to the railway vehicle, the roll direction being a rotational direction with the front-rear direction as a rotational axis, the conversion variable being a variable in which the angular displacement in the yaw direction of the wheel axle and the angular displacement in the yaw direction of the bogie are converted from each other, the track state deriving means derives an estimated value of the angular displacement in the yaw direction of the wheel axle using an actual value of the conversion variable as one of the state variables derived by the state variable deriving means, and deriving information reflecting a state of the track by using the derived estimated value of the angular displacement of the wheel axle in the yaw direction, wherein the actual value of the conversion variable is derived by using the measured value of the front-rear force, and wherein the state variable deriving means derives the state variable without using the measured value of the acceleration in the left-right direction of the bogie, the wheel axle, and the vehicle body during the period in which the measured value of the front-rear force is obtained.

The inspection method of the present invention is characterized by comprising: a data acquisition step of acquiring data of a measurement value of a force in the front-rear direction as data of a measurement value measured by running a railway vehicle having a vehicle body, a bogie, and an axle on a track; a state variable deriving step of deriving a state variable to be determined in a state equation configured by using a motion equation describing the motion of the railway vehicle, using the measured value of the front-rear force; and a track state deriving step of deriving information reflecting a state of the track, wherein the forward-backward force is a force in a forward-backward direction generated in a member disposed between the wheel axle and the bogie provided with the wheel axle, and is a force determined based on a difference between an angular displacement in a yaw direction of the wheel axle and an angular displacement in a yaw direction of the bogie provided with the wheel axle, the member is a member for supporting an axle box, the forward-backward direction is a direction along a traveling direction of the railway vehicle, the yaw direction is a rotational direction with a vertical direction perpendicular to the track as a rotational axis, and the state equation is an equation described using the state variable, the forward-backward force, and a conversion variable, the state variables include a displacement and a velocity in a left-right direction of the bogie, an angular displacement and an angular velocity in a yaw direction of the bogie, an angular displacement and an angular velocity in a roll direction of the bogie, a displacement and a velocity in a left-right direction of the wheel axle, and an angular displacement in a roll direction of an air spring attached to the railway vehicle, the roll direction being a rotational direction with the front-rear direction as a rotational axis, the conversion variable being a variable in which the angular displacement in the yaw direction of the wheel axle and the angular displacement in the yaw direction of the bogie are converted from each other, the track state deriving step derives an estimated value of the angular displacement in the yaw direction of the wheel axle using an actual value of the conversion variable as one of the state variables derived in the state variable deriving step, and deriving information reflecting a state of the track by using the derived estimated value of the angular displacement of the wheel axle in the yaw direction, wherein the actual value of the conversion variable is derived by using the measured value of the front-rear force, and wherein the state variable deriving step derives the state variable without using the measured value of the acceleration in the left-right direction of the bogie, the wheel axle, and the vehicle body during the period in which the measured value of the front-rear force is obtained.

The computer-readable storage medium of the present invention is characterized by storing a program that causes a computer to execute: a data acquisition step of acquiring data of a measurement value of a force in the front-rear direction as data of a measurement value measured by running a railway vehicle having a vehicle body, a bogie, and an axle on a track; a state variable deriving step of deriving a state variable to be determined in a state equation configured by using a motion equation describing the motion of the railway vehicle, using the measured value of the front-rear force; and a track state deriving step of deriving information reflecting a state of the track, wherein the forward-backward force is a force in a forward-backward direction generated in a member disposed between the wheel axle and the bogie provided with the wheel axle, and is a force determined based on a difference between an angular displacement in a yaw direction of the wheel axle and an angular displacement in a yaw direction of the bogie provided with the wheel axle, the member is a member for supporting an axle box, the forward-backward direction is a direction along a traveling direction of the railway vehicle, the yaw direction is a rotational direction with a vertical direction perpendicular to the track as a rotational axis, and the state equation is an equation described using the state variable, the forward-backward force, and a conversion variable, the state variables include a displacement and a velocity in a left-right direction of the bogie, an angular displacement and an angular velocity in a yaw direction of the bogie, an angular displacement and an angular velocity in a roll direction of the bogie, a displacement and a velocity in a left-right direction of the wheel axle, and an angular displacement in a roll direction of an air spring attached to the railway vehicle, the roll direction being a rotational direction with the front-rear direction as a rotational axis, the conversion variable being a variable in which the angular displacement in the yaw direction of the wheel axle and the angular displacement in the yaw direction of the bogie are converted from each other, the track state deriving step derives an estimated value of the angular displacement in the yaw direction of the wheel axle using an actual value of the conversion variable as one of the state variables derived in the state variable deriving step, the state variable deriving means derives the state variable without using the measured values of the acceleration in the left-right direction of the bogie, the wheel axle, and the vehicle body during the period in which the measured values of the front-rear direction force are obtained.

Drawings

Fig. 1 is a diagram showing an example of an outline of a railway vehicle.

Fig. 2 is a diagram conceptually showing the directions of main movements of the constituent elements of the railway vehicle.

Fig. 3 is a graph showing measured values and calculated values of acceleration in the left-right direction of the bogie and acceleration in the left-right direction of the wheel axle.

Fig. 4A is a diagram showing an example of the amount of end irregularities of a linear track.

Fig. 4B is a diagram showing an example of the amount of end irregularities of the curved track.

Fig. 5 is a diagram showing an example of the functional configuration of the inspection apparatus.

Fig. 6 is a diagram showing an example of a hardware configuration of the inspection apparatus.

Fig. 7 is a flowchart of an example of the processing of the inspection apparatus.

Fig. 8 is a diagram showing an example of the distribution of eigenvalues of the autocorrelation matrix.

Fig. 9 is a diagram showing an example of time-series data (measured value) of measured values of the force in the front-rear direction and time-series data (calculated value) of predicted values of the force in the front-rear direction.

Fig. 10 is a diagram showing an example of time-series data of high-frequency components of the force in the front-rear direction.

Fig. 11 is a diagram showing an example of the structure of the inspection system.

Fig. 12 is a diagram showing a calculation example, and shows a curvature 1/R of a track to be derived from the passing-end irregularity amount and a running speed of the railway vehicle.

Fig. 13A is a diagram showing a calculation example, and is a diagram showing example 1 of the distribution of eigenvalues of the autocorrelation matrix R.

Fig. 13B is a diagram showing a calculation example, and is a diagram showing example 2 of the distribution of eigenvalues of the autocorrelation matrix R.

Fig. 14 is a diagram showing a calculation example, and shows time-series data of measured values of the front-rear force and time-series data of predicted values of the front-rear force.

Fig. 15 is a diagram showing a calculation example, and is a diagram showing time-series data of high-frequency components of the front-rear direction force.

FIG. 16A is a diagram showing an example of calculation of the method according to embodiment 1, and shows the amount of open-end irregularities y _R Is shown in the figure of example 1.

FIG. 16B is a diagram showing an example of calculation of the method according to embodiment 1, and shows the amount of open-end irregularities y _R Is shown in the figure of example 2.

Fig. 17A is a diagram showing an example of calculation of the method according to embodiment 2, and shows the open-end irregularity y _R Is shown in the figure of example 1.

Fig. 17B is a diagram showing an example of calculation of the method according to embodiment 2, and shows the open-end irregularity y _R Is shown in the figure of example 2.

Detailed Description

Hereinafter, embodiments of the present invention will be described with reference to the drawings.

(conception)

First, the idea obtained by the present inventors when implementing the embodiment of the present invention will be described.

Fig. 1 is a diagram showing an example of an outline of a railway vehicle. In fig. 1, the railway vehicle advances in the forward direction of the x-axis (the x-axis is an axis along the traveling direction of the railway vehicle). The z-axis is a direction perpendicular to the rail 16 (ground) (the height direction of the railway vehicle). The y-axis is a horizontal direction perpendicular to the running direction of the railway vehicle (a direction perpendicular to both the running direction and the height direction of the railway vehicle). In addition, the railway vehicle is a business vehicle. In each of the drawings, +'s are added to the plane of o to indicate the direction from the back side of the sheet to the front side, and ×'s are added to the plane of o to indicate the direction from the front side of the sheet to the back side.

As shown in fig. 1, in the present embodiment, the railway vehicle includes a vehicle body 11, bogies 12a, 12b, and axles 13a to 13d. As described above, in the present embodiment, a railway vehicle in which one vehicle body 11 includes two bogies 12a, 12b and 4 sets of axles 13a to 13d will be described as an example. The axles 13a to 13d have axles 15a to 15d and wheels 14a to 14d provided at both ends thereof. In the present embodiment, the description will be given taking, as an example, a case where the bogies 12a, 12b are shaftless bogies. In fig. 1, only one of the wheels 14a to 14d of the wheel shafts 13a to 13d is shown for convenience of description, but wheels (8 wheels in total in the example shown in fig. 1) are provided on the other of the wheel shafts 13a to 13d. The railway vehicle has components other than the components shown in fig. 1 (components described in the motion equations described below, etc.), but for convenience of description, illustration of the components is omitted in fig. 1. For example, the bogies 12a, 12b have a bogie frame, a tie spring, and the like. Axle boxes are disposed on both sides of each of the axles 13a to 13d in the y-axis direction. The bogie frame and the axle box are coupled to each other by an axle box supporting device. The axle box supporting device is a device (suspension) disposed between the axle box and the bogie frame. The axlebox support device absorbs vibrations transmitted from the rail 16 to the railway vehicle. The axle box supporting device supports the axle box with the position of the axle box relative to the bogie frame restricted so as to suppress the movement of the axle box relative to the bogie frame in the x-axis direction and the y-axis direction (preferably, without causing the movement). The axle box supporting devices are disposed on both sides of each of the axles 13a to 13d in the y-axis direction. The railway vehicle itself can be realized by a known technique, and therefore, a detailed description thereof will be omitted here.

When the railway vehicle runs on the rail 16, the acting force (creep force) between the wheels 14a to 14d and the rail 16 becomes a vibration source, and the vibration is transmitted to the wheel axles 13a to 13d, the bogies 12a, 12b, and the vehicle body 11 in this order. Fig. 2 is a diagram conceptually showing the main movement directions of the constituent elements (the axles 13a to 13d, the bogies 12a, 12b, and the vehicle body 11) of the railway vehicle. The x-axis, y-axis, and z-axis shown in fig. 2 correspond to the x-axis, y-axis, and z-axis shown in fig. 1, respectively.

As shown in fig. 2, in the present embodiment, a case will be described in which the axles 13a to 13d, the bogies 12a, 12b, and the vehicle body 11 perform a movement that rotates about the x-axis, a movement that rotates about the z-axis, and a movement in the direction along the y-axis. In the following description, a motion of rotating about the x-axis as a rotation axis is referred to as a roll as needed, a rotation direction of rotating about the x-axis as a rotation axis is referred to as a roll direction as needed, and a direction along the x-axis is referred to as a front-rear direction as needed. The front-rear direction is the traveling direction of the railway vehicle. In the present embodiment, the direction along the x-axis is the running direction of the railway vehicle. The movement of the rotation about the z axis as the rotation axis is referred to as yaw if necessary, the rotation direction about the z axis as the rotation axis is referred to as yaw if necessary, and the direction along the z axis is referred to as up-down direction if necessary. The vertical direction is a direction perpendicular to the rail 16. The movement in the y-axis direction is referred to as lateral vibration as needed, and the y-axis direction is referred to as left-right direction as needed. The left-right direction is a direction perpendicular to both the front-rear direction (the running direction of the railway vehicle) and the up-down direction (the direction perpendicular to the rail 16). In addition, the railway vehicle performs other motions, but these motions are not considered for simplicity of description in each embodiment. However, these movements are also contemplated.

[ 1 st conception ]

In the technique described in patent document 1, the acceleration y in the left-right direction of the axles 13a, 13b, 13c, 13d is calculated _w1 ··、y _w2 ··、y _w3 ··、y _w4 The acceleration y in the left-right direction of the trucks 12a, 12b _t1 ··、y _t2 Further, acceleration y in the left-right direction of the vehicle body 11 is set as required _b As an observation variable, a filter (kalman filter) for data assimilation was used to filter the data, and a state variable was derived therefrom.

Fig. 3 shows the acceleration y in the left-right direction of the bogie 12a _t1 Acceleration y in the left-right direction of the axles 13a, 13b _w1 ··、y _w2 Measurement values and calculation values of each. The calculated value is an estimated value of the observed variable calculated by data assimilation. Drawing of the figureThe horizontal axis of 3 is the elapsed time (seconds) from the reference time when the reference time is set to 0 (zero). Specifically, the horizontal axis of fig. 3 represents the acceleration y in the left-right direction of the bogie 12a _t1 The acceleration y in the left-right direction of the axles 13a, 13b _w1 ··、y _w2 Measurement time and calculation time of·. In data assimilation, the estimated value of the state variable is derived so that an error between a value originally given as a measured value of the observed variable and the estimated value is minimized or an expected value of the error is minimized.

As shown in fig. 3, the acceleration y in the left-right direction of the wheel shafts 13a, 13b _w1 ··、y _w2 Measurement value of··acceleration y in left-right direction of bogie 12a _t1 The measurement value of·contains much noise. Based on this, the present inventors have found that: depending on the state of the track 16 (rail bar), even if data assimilation is performed, the estimated value does not come close to the measured value and becomes a substantially constant value. In this case, the acceleration y in the left-right direction of the wheel shafts 13c, 13d _w3 ··、y _w4 Acceleration y in the left-right direction of the bogie 12b _t2 And acceleration y in the left-right direction of the vehicle body 11 _b The same applies to the same. In this case, the present inventors considered whether or not the end irregularity y can be derived without greatly decreasing the accuracy even if these measured values of acceleration are not used in deriving the state variable _R1 、y _R2 、y _R3 、y _R4 。

[ 2 nd conception ]

As described in patent document 1, the present inventors have conceived the following method: the amount of the through-end irregularities is calculated using measured values of forces in the front-rear direction generated in members disposed between the wheel axles 13a to 13b (13 c to 13 d) and the trucks 12a (12 b) provided with the wheel axles 13a to 13b (13 c to 13 d). In the following description, the force in the front-rear direction generated in the member is referred to as a front-rear direction force as needed.

The passing end irregularity amount is calculated using a formula based on a motion equation describing a motion of the railway vehicle when traveling on a straight track, and a formula representing a relationship between the passing end irregularity amount and the front-rear direction force. The track 16 includes a straight portion and a curved portion. In the following description, the linear portion of the track 16 will be referred to as a linear track as needed, and the curved portion of the track 16 will be referred to as a curved track as needed.

In the case of filtering by a filter (kalman filter) that performs data assimilation, when a state equation is constructed using a motion equation describing the motion of a railway vehicle traveling on a curved track, there is a possibility that a state variable diverges. Therefore, an equation of motion describing the motion of a railway vehicle traveling on a straight track is used to construct an equation of state in the case of filtering by a filter (kalman filter) that performs data assimilation.

In the motion equation describing the motion of a railway vehicle traveling on a curved track, it is necessary to consider centrifugal force and the like to which the railway vehicle is subjected during traveling. Thus, the motion equation describing the motion of the railway vehicle traveling on the curved track includes a term including the radius of curvature of the rail (rail). Therefore, when a railway vehicle runs on a curved track, it is possible that the state variable cannot be derived with high accuracy when a filter (kalman filter) configured by using a motion equation describing the motion of the railway vehicle running on a straight track and performing data assimilation is used to derive the state variable.

The present inventors focused on the following cases: when the railway vehicle runs on a curved track, the measured value of the force in the front-rear direction is offset by a certain amount from the measured value of the force when running on a straight track. The component of the front-rear direction force itself due to the open-end irregularity is generated similarly in both the curved track and the straight track. Accordingly, the present inventors considered that the amount of the through-end irregularity itself is not related to the amount of the offset, and by reducing the low frequency component (behavior of the offset) from the time-series data of the measured values of the forces in the front-rear direction, even if a filter (kalman filter) for data assimilation is configured using a formula based on a motion equation describing the motion of the railway vehicle when traveling on a straight track, the low frequency component due to the railway vehicle traveling on a curved track can be reduced from the estimated value of the state variable. From this, the present inventors thought that: the amount of open-end irregularities is calculated using time-series data of values of the front-rear direction force reduced by the low frequency component. By calculating the open-end irregularity amount in this manner, the open-end irregularity amount of the curved track can be calculated even if a formula based on a motion equation describing the motion of the railway vehicle when traveling on the straight track is used. The calculation formula of the end irregularity is the same as that of the straight line track or the curved line track. Even if the track is a straight track in design, there is a case where the track has a curvature that affects the estimation accuracy of the through-end irregularity in practice. Therefore, not only in the curved trajectory, but also in the straight trajectory, the low frequency component (the behavior of the offset) is reduced from the time-series data of the measured value of the force in the front-rear direction, which contributes to the improvement of the estimation accuracy of the through-end irregularity. Hereinafter, a track that is a straight track in design but actually has curvature to such an extent that the estimation accuracy of the passing-end irregularity is affected will be described as a curved track.

(equation of motion)

Next, an example of an equation of motion describing the motion of the railway vehicle will be described. In the present embodiment, the equation of motion described in patent document 1 is taken as an example, and a case where the railway vehicle has 21 degrees of freedom is taken as an example. That is, the wheel shafts 13a to 13d perform movement (lateral vibration) in the left-right direction and movement (deflection) in the deflection direction (2×4 group=8 degrees of freedom). The bogies 12a, 12b perform a motion in the left-right direction (lateral vibration), a motion in the yaw direction (yaw), and a motion in the roll direction (roll) (3×2 group=6 degrees of freedom). Further, the vehicle body 11 performs a motion in the left-right direction (lateral vibration), a motion in the yaw direction (yaw), and a motion in the roll direction (roll) (3×1 group=3 degrees of freedom). Further, the air springs (springs) provided to the bogies 12a, 12b respectively perform movement (rolling) in the rolling direction (1×2 group=2 degrees of freedom). Further, the yaw dampers provided to the bogies 12a, 12b respectively perform motions (yaw) in the yaw direction (1×2 groups=2 degrees of freedom).

The degrees of freedom are not limited to 21 degrees of freedom. If the degree of freedom is increased, the calculation accuracy is improved, but the calculation load becomes high. Further, the operation of the kalman filter described later may become unstable. The degree of freedom can be appropriately determined in consideration of these aspects. Further, for example, by expressing the operations in the respective directions (the left-right direction, the yaw direction, and the roll direction) of the respective constituent elements (the vehicle body 11, the bogies 12a, 12b, and the axles 13a to 13 d) based on the description of patent literature 1, the following equation of motion can be realized. Therefore, the outline of each equation of motion will be described here, and detailed description will be omitted. In the following formulae, no term including the radius of curvature (curvature) of the rail 16 (rail bar) exists. That is, the following equations represent the running of the railway vehicle on the linear rail. In the expression for expressing that the railway vehicle is traveling on the curved track, the curvature radius of the track 16 (rail bar) is set to infinity (curvature is 0 (zero)), and the expression for expressing that the railway vehicle is traveling on the straight track can be obtained.

In the following formulae, the subscript w denotes the axles 13a to 13d. The variable representation (only) with the subscript w attached is common among the axles 13 a-13 d. The subscripts w1, w2, w3, w4 denote the axles 13a, 13b, 13c, 13d, respectively.

The subscripts T, T denote bogies 12a, 12b. The variable representations (only) with subscripts T, T attached are common in the bogies 12a, 12b. Subscripts t1, t2 denote bogies 12a, 12b, respectively.

The subscripts B, B denote the vehicle body 11.

The subscript x indicates the front-rear direction or the roll direction, the subscript y indicates the left-right direction, and the subscript z indicates the up-down direction or the yaw direction.

Further, "·", "" attached to the variables represent the 2 nd order time differential and the 1 st order time differential, respectively.

In the following description of the equation of motion, the description of the variables that have been presented will be omitted, if necessary. The equation of motion itself is the same as the equation of motion described in patent document 1.

[ transverse vibration of axle ]

Equations of motion describing lateral vibrations (movement in the left-right direction) of the axles 13a to 13d are expressed by the following equations (1) to (4).

[ number 1]

m _w Is the mass of the axles 13 a-13 d. y is _w1 (in the formula, & is appended to y _w1 The upper (hereinafter, the same applies to other variables)) is the acceleration in the left-right direction of the wheel shaft 13 a. f (f) ₂ Is the transverse creep coefficient (in addition, the transverse creep coefficient f ₂ Or may be assigned to each axle 13 a-13 d). V is the running speed of the railway vehicle. y is _w1 (in the formula, attached to y _w1 The upper (hereinafter, the same applies to other variables)) is the speed of the wheel shaft 13a in the left-right direction. C (C) _wy Is a damping constant in the left-right direction of an axle housing supporting device connecting an axle housing to an axle. y is _t1 Is the speed of the bogie 12a in the left-right direction. a represents 1/2 of the distance in the front-rear direction between the wheel axles 13a, 13b, 13c, 13d provided in the bogies 12a, 12b (the distance between the wheel axles 13a, 13b, 13c, 13d provided in the bogies 12a, 12b is 2 a). Psi phi type _t1 In the direction of deflection of bogie 12aAngular velocity. h is a ₁ Is the distance in the up-down direction between the center of the axle and the center of gravity of the bogie 12 a.Is the angular velocity of the bogie 12a in the roll direction. Psi phi type _w1 Is the amount of rotation (angular displacement) in the yaw direction of the wheel shaft 13 a. K (K) _wy Is the spring constant of the axle box supporting device in the left-right direction. y is _w1 Is the displacement in the left-right direction of the wheel shaft 13 a. y is _t1 Is displacement in the left-right direction of the bogie 12 a. Psi phi type _t1 Is the amount of rotation (angular displacement) in the yaw direction of the bogie 12 a. />Is the amount of rotation (angular displacement) in the roll direction of the bogie 12 a. Further, the variables of the formulas (2) to (4) are represented by replacing the variables of the formula (1) by the meanings of the subscripts.

[ deflection of wheel axle ]

The equation of motion describing the deflection of the axles 13a to 13d is expressed by the following equations (5) to (8).

[ number 2]

I _wz Is the moment of inertia in the yaw direction of the axles 13 a-13 d. Psi phi type _w1 The direction of deflection of the wheel shaft 13aAngular acceleration at upper. f (f) ₁ Is the longitudinal creep coefficient. b is a distance in the left-right direction between the tangential points of the two wheels attached to the axles 13a to 13d and the rail 16 (rail bar). Psi phi type _w1 Is the angular velocity in the yaw direction of the axle 13 a. C (C) _wx Is the damping constant of the axle box supporting device in the front-rear direction. b ₁ A length of 1/2 of a distance between the axle box supporting devices in the left-right direction (a distance between the axle box supporting devices provided on the left and right with respect to one axle is 2 b) ₁ ). Gamma is the tread gradient. r is the radius of the wheels 14 a-14 d. y is _R1 Is the amount of through-end irregularity at the location of the axle 13 a. s is(s) _a Is the amount of bias in the front-rear direction from the center of the axle shafts 15a to 15d to the axle box supporting springs. y is _t1 Is displacement in the left-right direction of the bogie 12 a. K (K) _wx Is the spring constant of the axle box supporting device in the front-rear direction. Further, the variables of the formulas (6) to (8) are represented by replacing the variables of the formula (5) by the meanings of the subscripts. Wherein y is _R2 、y _R3 、y _R4 The amount of end irregularities at the location of the axles 13b, 13c, 13d, respectively.

Here, the irregular through end means a displacement of the rail in the longitudinal direction as described in japanese industrial standard (JIS E1001:2001). The amount of open-end irregularity is the amount of this displacement. Fig. 4A and 4B show the through-end irregularity y at the position of the wheel axle 13a _R1 As an example of (a) is described. In fig. 4A, a case where the rail 16 is a straight rail is described as an example. In fig. 4B, a case where the track 16 is a curved track is illustrated as an example. In fig. 4A and 4B, 16a represents a rail and 16B represents a sleeper. In fig. 4A, the wheel 14A of the axle 13a is in contact with the rail 16a at a location 401. In fig. 4B, the wheel 14a of the axle 13a is in contact with the rail 16a at location 402. Through-end irregularity y at the location of axle 13a _R1 Is the distance in the left-right direction between the contact position of the wheel 14a of the wheel axle 13a with the rail 16a and the position of the rail 16a in the case where the normal state is assumed. The position of the axle 13a is the contact position of the wheel 14a of the axle 13a with the rail 16 a. Through irregularities y at the location of the axles 13b, 13c, 13d _R2 、y _R3 、y _R4 Also with the through-end irregularities y at the location of the axle 13a _R1 And is defined as such.

[ transverse vibration of bogie ]

Equations of motion describing lateral vibrations (movement in the left-right direction) of the bogies 12a, 12b are expressed by the following equations (9) and (10).

[ number 3]

m _T Is the mass of the trucks 12a, 12 b. y is _t1 The term "·is the acceleration in the left-right direction of the bogie 12 a. c' ₂ Is the damping constant of the left-right movement damper. h is a ₄ Is the distance between the center of gravity of the bogie 12a and the left-right movement damper in the up-down direction. y is _b Is the speed of the vehicle body 11 in the left-right direction. L represents 1/2 of the interval in the front-rear direction between the centers of the bogies 12a, 12b (the interval in the front-rear direction between the centers of the bogies 12a, 12b is 2L). Psi phi type _b Is the angular velocity in the yaw direction of the vehicle body 11. h is a ₅ Is the distance in the up-down direction between the left-right movement damper and the center of gravity of the vehicle body 11.Is the angular velocity of the vehicle body 11 in the roll direction. y is _w2 Is the speed in the left-right direction of the wheel shaft 13 b. k' ₂ Is the spring constant of the air spring (pillow spring) in the left-right direction. h is a ₂ Is the distance in the up-down direction between the center of gravity of the trucks 12a, 12b and the center of the air spring (tie spring). y is _b Is displacement in the left-right direction of the vehicle body 11. Psi phi type _b Is the amount of rotation (angular displacement) in the yaw direction of the vehicle body 11. h is a ₃ Is the distance in the up-down direction between the center of the air spring (pillow) and the center of gravity of the vehicle body 11./>Is the rotation amount (angular displacement) in the roll direction of the vehicle body 11. Further, the variables of the formula (9) are replaced by the meanings of the subscripts described above, whereby the variables of the formula (10) are represented.

[ deflection of bogie ]

The equation of motion describing the deflection of the bogies 12a, 12b is expressed by the following expression (11) and expression (12).

[ number 4]

I _Tz Is the moment of inertia in the yaw direction of the bogies 12a, 12 b. Psi phi type _t1 And··is the angular acceleration in the yaw direction of the bogie 12 a. Psi phi type _w2 Is the angular velocity in the yaw direction of the axle 13 b. Psi phi type _w2 Is the amount of rotation (angular displacement) in the yaw direction of the wheel shaft 13 b. y is _w2 Is the displacement in the left-right direction of the wheel shaft 13 b. k' ₀ Is the rubber bushing stiffness of the yaw damper. b' ₀ 1/2 of the interval in the left-right direction between the two yaw dampers arranged on the left and right with respect to the bogies 12a, 12b (the interval in the left-right direction between the two yaw dampers arranged on the left and right with respect to the bogies 12a, 12b is 2b '' ₀ )。ψ _y1 Is the amount of rotation (angular displacement) in the yaw direction of the yaw damper disposed in the bogie 12 a. k' ₂ Is the spring constant of the air spring (pillow spring) in the front-rear direction. b ₂ 1/2 of the interval in the left-right direction between the two air springs (springs) arranged on the left and right with respect to the bogies 12a, 12b (the interval in the left-right direction between the two air springs (springs) arranged on the left and right with respect to the bogies 12a, 12b is 2 b) ₂ ). In addition, by substituting the meaning of the subscript as described above(11) The variables of the formula (12) are represented by the variables of the formula (i).

[ roll of bogie ]

The equation of motion describing the roll of the bogies 12a, 12b is expressed by the following expression (13) and expression (14).

[ number 5]

I _Tx Is the moment of inertia in the roll direction of the bogies 12a, 12 b.Is the angular acceleration in the roll direction of the bogie 12 a. c1 is a damping constant in the up-down direction of the shaft damper. b' ₁ 1/2 of the interval in the left-right direction between the two axle dampers arranged on the left and right sides with respect to the bogies 12a, 12b (the interval in the left-right direction between the two axle dampers arranged on the left and right sides with respect to the bogies 12a, 12b is 2b' ₁ )。c ₂ Is the damping constant of the air spring (pillow spring) in the up-down direction.Is the angular velocity in the rolling direction of the air springs (springs) disposed in the bogie 12 a. k (k) ₁ Is the spring constant of the shaft spring in the up-down direction. Lambda is a value obtained by dividing the volume of the main body of the air spring (pillow) by the volume of the auxiliary air chamber. k (k) ₂ Is the spring constant of the air spring (pillow spring) in the up-down direction. />Is the rotation amount (angular displacement) in the rolling direction of the air springs (springs) disposed in the bogie 12 a. k (k) ₃ Is based on the equivalent stiffness of the change of the effective pressure-receiving area of the air spring (sleeper spring)Sex. Further, the variables of the formula (13) are replaced by the meanings of the subscripts described above, whereby the variables of the formula (14) are represented. Wherein,is the rotation amount (angular displacement) in the rolling direction of the air springs (springs) disposed in the bogie 12 b.

[ transverse vibration of vehicle body ]

The equation of motion describing the lateral vibration (movement in the left-right direction) of the vehicle body 11 is expressed by the following expression (15).

[ number 6]

m _B Is the mass of the trucks 12a, 12 b. y is _b The term "·is the acceleration in the lateral direction of the vehicle body 11. y is _t2 Is the speed of the bogie 12b in the left-right direction.Is the angular velocity of the bogie 12b in the roll direction. y is _t2 Is displacement in the left-right direction of the bogie 12 b. />Is the amount of rotation (angular displacement) of the bogie 12b in the roll direction.

[ deflection of vehicle body ]

The equation of motion describing the deflection of the vehicle body 11 is expressed by the following expression (16).

[ number 7]

I _Bz Is the moment of inertia in the yaw direction of the vehicle body 11. Psi phi type _b The term "·is the angular acceleration in the yaw direction of the vehicle body 11. c ₀ Is the damping constant of the yaw damper in the front-rear direction. Psi phi type _y1 Is the angular velocity in the yaw direction of the yaw damper disposed on the bogie 12 a. Psi phi type _y2 Is the angular velocity in the yaw direction of the yaw damper disposed on the bogie 12 b. Psi phi type _t2 Is the amount of rotation (angular displacement) in the yaw direction of the bogie 12 b.

[ roll of vehicle body ]

The equation of motion describing the roll of the vehicle body 11 is expressed by the following expression (17).

[ number 8]

I _Bx Is the moment of inertia in the yaw direction of the vehicle body 11.Is the angular acceleration in the roll direction of the vehicle body 11.

Deflection of deflection damper

Equations describing the deflection of the deflection damper disposed on the bogie 12a and the deflection damper disposed on the bogie 12b are expressed by the following equations (18) and (19), respectively.

[ number 9]

ψ _y2 Is the amount of rotation (angular displacement) in the yaw direction of the yaw damper disposed in the bogie 12 b.

[ roll of air spring (pillow spring) ]

Equations describing the roll motions of the air springs (springs) disposed in the bogie 12a and the air springs (springs) disposed in the bogie 12b are expressed by the following equations (20) and (21), respectively.

[ number 10]

Is the angular velocity in the rolling direction of the air springs (springs) disposed in the bogie 12 b.

(force in front-rear direction)

Next, the front-rear direction force will be described. The front-rear force itself is the same as the front-rear force described in patent document 1.

The component of the longitudinal creep force of one of the left and right wheels on one wheel axle, which is in phase with the longitudinal creep force of the other wheel, is a component corresponding to braking force or driving force. Thus, the front-rear direction force is preferably determined in a manner corresponding to the inverted component of the longitudinal creep force. The opposite phase component of the longitudinal creep force is a component in which the longitudinal creep force of one of the left and right wheels on one wheel axle and the longitudinal creep force of the other wheel are opposite to each other. That is, the inverted component of the longitudinal creep force means a component of the longitudinal creep force in a direction in which the axle is twisted. In this case, the front-rear direction force is a component in which the front-rear direction force is opposite to the front-rear direction force generated by the two members attached to the left-right direction of the one wheel axle.

Hereinafter, a specific example of the longitudinal force in the case where the longitudinal force is determined so as to correspond to the opposite phase component of the longitudinal creep force will be described.

In the case where the axle box supporting device is a single link type axle box supporting device, the axle box supporting device includes a link, and the axle box and the bogie frame are coupled by the link. Rubber bushings are mounted at both ends of the connecting rod. In this case, the front-rear direction force is a component of the front-rear direction of the load received by each of the two links mounted on the left-right direction end portion of the one wheel axle, the components being opposite to each other. Further, depending on the arrangement and configuration of the links, the links mainly receive loads in the front-rear direction, among loads in the front-rear direction, the left-right direction, and the up-down direction. Thus, for example, one strain gauge may be attached to each link. The longitudinal force measurement value is obtained by deriving the longitudinal component of the load applied to the link using the measurement value of the strain gauge. In addition, instead of this, the displacement in the front-rear direction of the rubber bush attached to the link may be measured by a displacement meter. In this case, the product of the measured displacement and the spring constant of the rubber bushing is set as a measured value of the front-rear force. In the case where the axlebox support device is a single link axlebox support device, the above-described member for supporting the axlebox is a link or a rubber bushing.

In addition, the load measured by the strain gauge attached to the connecting rod may include not only a component in the front-rear direction but also at least one of a component in the left-right direction and a component in the up-down direction. However, even in this case, in the structure of the axle box supporting apparatus, the load of the component in the left-right direction and the load of the component in the up-down direction, which are received by the link, are sufficiently smaller than the load of the component in the front-rear direction. Therefore, by only attaching one strain gauge to each link, a measured value of the front-rear force having practically required accuracy can be obtained. As described above, the measured value of the force in the front-rear direction may include a component other than the component in the front-rear direction. Therefore, 3 or more strain gauges may be attached to each link so as to relieve strain in the up-down direction and the left-right direction. In this way, the accuracy of the measurement value of the front-rear force can be improved.

In the case where the axlebox support device is an axlebox support device of an axlebox type, the axlebox support device includes an axlebox, and the axlebox and the bogie frame are coupled by the axlebox. The axle beam may also be integrally formed with the axle housing. A rubber bushing is attached to the end of the axle beam on the bogie frame side. In this case, the front-rear direction force is a component of the front-rear direction of the load received by the two axle beams, each of which is attached to each of the left-right direction ends of one axle, and is opposite to each other. Further, according to the arrangement configuration of the axle beam, the axle beam receives not only the load in the front-rear direction, but also the load in the left-right direction among the loads in the front-rear direction, the left-right direction, and the up-down direction. Thus, for example, two or more strain gauges are attached to each axle beam so as to relieve strain in the left-right direction. The front-rear force measurement value is obtained by deriving the front-rear direction component of the load applied to the axle beam using the measurement values of the strain gauges. In addition, instead of this, the displacement in the front-rear direction of the rubber bush attached to the axle beam may be measured by a displacement meter. In this case, the product of the measured displacement and the spring constant of the rubber bushing is set as a measured value of the front-rear force. In the case where the axlebox bearing device is an axlebox bearing device, the above-described member for bearing the axlebox is an axlebox or a rubber bushing.

In addition, the load measured by the strain gauge attached to the axle beam may include not only components in the front-rear direction and the left-right direction, but also components in the up-down direction. However, even in this case, in the structure of the axlebox supporting device, the load of the component in the up-down direction, which the axle beam receives, is sufficiently smaller than the load of the component in the front-rear direction and the load of the component in the left-right direction. Therefore, even if the strain gauge is not attached so as to eliminate the load of the component in the up-down direction received by the axle beam, the measured value of the front-rear direction force with the accuracy required for practical use can be obtained. In this way, the measured longitudinal force may include components other than the longitudinal components, and 3 or more strain gauges may be attached to each of the axle beams so as to cancel the strain in the vertical direction in addition to the strain in the horizontal direction. In this way, the accuracy of the measurement value of the front-rear force can be improved.

In the case where the axle box supporting device is a leaf spring type axle box supporting device, the axle box supporting device includes a leaf spring, and the axle box and the bogie frame are coupled by the leaf spring. A rubber bushing is attached to an end of the leaf spring. In this case, the front-rear direction force is a component of the front-rear direction of the load received by the two leaf springs, each of which is attached to the end portion of one wheel axle in the left-right direction, and is opposite in phase to each other. Further, according to the arrangement configuration of the leaf springs, the leaf springs are susceptible to load in the lateral direction and load in the vertical direction in addition to load in the longitudinal direction out of load in the longitudinal direction, the lateral direction, and the vertical direction. Thus, for example, 3 or more strain gauges are attached to each leaf spring so as to relieve strain in the left-right direction and the up-down direction. The front-rear force measurement value is obtained by deriving the front-rear direction component of the load applied to the leaf spring using the measurement values of the strain gauges. In addition, instead of this, the displacement in the front-rear direction of the rubber bush attached to the leaf spring may be measured by a displacement meter. In this case, the product of the measured displacement and the spring constant of the rubber bushing is set as a measured value of the front-rear force. In the case where the axle box supporting device is a leaf spring type axle box supporting device, the above-described member for supporting the axle box is a leaf spring or a rubber bushing.

As the displacement meter, a known laser displacement meter or an eddy current displacement meter can be used.

Here, the case where the pedestal supporting device is of the single link type, the axle beam type, and the leaf spring type will be described as an example. However, the type of the axlebox support device is not limited to the single link type, the axle beam type, and the leaf spring type. According to the aspect of the axlebox support device, the front-rear direction force can be determined in the same manner as the single link, the axle beam, and the leaf spring.

In the following, for simplicity of explanation, a case where one measurement value of the force in the front-rear direction is obtained for one wheel axle will be described as an example. That is, the railway vehicle shown in fig. 1 has 4 wheel axles 13a to 13d. Thus, 4 front-rear direction forces T are obtained ₁ ～T ₄ Is measured by the above method.

(embodiment 1)

Next, embodiment 1 of the present invention will be described.

< inspection device 500>

Fig. 5 is a diagram showing an example of a functional configuration of the inspection apparatus 500. Fig. 6 is a diagram showing an example of a hardware configuration of the inspection apparatus 500. Fig. 7 is a flowchart showing an example of the processing of the inspection apparatus 500. In the present embodiment, as shown in fig. 1, a case where an inspection device 500 is mounted on a railway vehicle is illustrated as an example.

In fig. 5, the inspection apparatus 500 includes, as its functions, a storage unit 501, a data acquisition unit 502, a 1 st frequency adjustment unit 503, a state variable derivation unit 504, a 2 nd frequency adjustment unit 505, a track state derivation unit 506, and an output unit 507.

In fig. 6, the inspection apparatus 500 has a CPU601, a main storage 602, an auxiliary storage 603, a communication circuit 604, a signal processing circuit 605, an image processing circuit 606, an I/F circuit 607, a user interface 608, a display 609, and a bus 610.

The CPU601 comprehensively controls the entire inspection apparatus 500. The CPU601 uses the main storage 602 as a work area, and executes a program stored in the auxiliary storage 603. The main storage 602 temporarily stores data. The auxiliary storage device 603 stores various data in addition to programs executed by the CPU 601. The auxiliary storage device 603 stores a state equation and an observation equation described later. The storage unit 501 is realized by using, for example, a CPU601 and an auxiliary storage device 603.

The communication circuit 604 is a circuit for communicating with the outside of the inspection apparatus 500. The communication circuit 604 receives information of a measured value of the front-rear force, for example. The communication circuit 604 may perform wireless communication or wired communication with the outside of the inspection apparatus 500. The communication circuit 604 is connected to an antenna provided in the railway vehicle when performing wireless communication.

The signal processing circuit 605 performs various signal processing on the signal received by the communication circuit 604 and the signal input in accordance with the control performed by the CPU 601. The data acquisition unit 502 is implemented by using, for example, a CPU601, a communication circuit 604, and a signal processing circuit 605. The 1 st frequency adjustment unit 503, the state variable derivation unit 504, the 2 nd frequency adjustment unit 505, and the track state derivation unit 506 are realized by using, for example, a CPU601 and a signal processing circuit 605.

The image processing circuit 606 performs various image processing on signals input in accordance with control performed by the CPU 601. The signal subjected to the image processing is output to the display 609.

The user interface 608 is a part of an operator that instructs the inspection apparatus 500. The user interface 608 has, for example, buttons, switches, dials, and the like. In addition, the user interface 608 may also have a graphical user interface using a display 609.

The display 609 displays an image based on a signal output from the image processing circuit 606. The I/F circuit 607 exchanges data between devices connected to the I/F circuit 607. In fig. 6, a user interface 608 and a display 609 are shown as devices connected to the I/F circuit 607. However, the device connected to the I/F circuit 607 is not limited to these. For example, a portable storage medium may also be connected to the I/F circuit 607. Furthermore, at least a portion of the user interface 608 and the display 609 may also be external to the inspection device 500.

The output unit 507 is realized by using at least one of the communication circuit 604, the signal processing circuit 605, the image processing circuit 606, the I/F circuit 607, and the display 609, for example.

Further, a CPU601, a main memory device 602, an auxiliary memory device 603, a signal processing circuit 605, an image processing circuit 606, and an I/F circuit 607 are connected to a bus 610. Communication between these constituent elements is performed via a bus 610. The hardware of the inspection apparatus 500 is not limited to the hardware shown in fig. 6, as long as the functions of the inspection apparatus 500 described below can be realized.

[ storage section 501]

The storage unit 501 stores an equation used by the state variable derivation unit 504 to be described later when deriving a state variable.

In the present embodiment, the storage unit 501 stores a state equation and an observation equation.

In this embodiment, a case will be described in which a state equation and an observation equation described in patent document 1 are used as an example.

First, a state equation will be described.

In the present embodiment, the equations (5) to (8) (equations of motion describing the deflections of the axles 13a to 13 d) are not included in the equations of state, but the equations of state are configured as follows.

First, the equations of the state are used directly for equations (9), (10) (equations of motion describing the lateral vibrations (movement in the left-right direction) of the trucks 12a, 12 b), (13), (14) (equations of motion describing the roll of the trucks 12a, 12 b), (15) (equations of motion describing the lateral vibrations (movement in the left-right direction) of the vehicle body 11), (16) (equations of motion describing the deflection of the vehicle body 11), (17) (equations of motion describing the roll of the vehicle body 11), (18), (19) (equations of motion describing the deflection damper disposed on the truck 12a and the deflection damper disposed on the truck 12 b), (20), (21) (equations of motion describing the roll of the air springs (pillow springs) disposed on the truck 12a and the air springs (pillow springs) disposed on the truck 12 b).

On the other hand, the expression (1) to (4) (equation of motion describing the lateral vibration (movement in the left-right direction) of the axles 13a to 13 d), (11) and (12) (equation of motion describing the deflection of the bogies 12a, 12 b) include the rotation amounts (angular displacements) ψ in the deflection directions of the axles 13a to 13d _w1 ～ψ _w4 Angular velocity ψ _w1 ·～ψ _w4 And (3) the process. The state equation is constructed using a formula obtained by eliminating these variables from the formulas (1) to (4) and (11) and (12).

First, the front-rear direction force T of the axles 13a to 13d ₁ ～T ₄ The expression (22) to (25) below. Thus, according to the angular displacement psi of the deflection direction of the wheel axle _w1 ～ψ _w4 Angular displacement ψ from the yaw direction of the bogie provided with the axle _t1 ～ψ _t2 The difference determines the front-back direction force T ₁ ～T ₄ 。

[ number 11]

The conversion variable e is defined as in the following formulas (26) to (29) ₁ ～e ₄ . Thus, by the angular displacement ψ of the yaw direction of the bogie _t1 ～ψ _t2 Angular displacement psi from the direction of deflection of the axle _w1 ～ψ _w4 The difference defines the conversion variable e ₁ ～e ₄ . Conversion variable e ₁ ～e ₄ Is an angular displacement psi for deflecting the bogie in the direction of deflection _t1 ～ψ _t2 Angular displacement psi from the direction of deflection of the axle _w1 ～ψ _w4 Variables that are converted to each other.

[ number 12]

e ₁ ＝ψ _t1 -ψ _w1 …(26)

e ₂ ＝ψ _t1 -ψ _w2 …(27)

e ₃ ＝ψ _t2 -ψ _w3 …(28)

e ₄ ＝ψ _t2 -ψ _w4 …(29)

When the formulas (26) to (29) are modified, the following formulas (30) to (33) are obtained.

[ number 13]

ψ _w1 ＝ψ _t1 -e ₁ …(30)

ψ _w2 ＝ψ _t1 -e ₂ …(31)

ψ _w3 ＝ψ _t2 -e ₃ …(32)

ψ _w4 ＝ψ _t2 -e ₄ …(33)

When equations (30) to (33) are substituted into equations of motion describing lateral vibrations (movement in the left-right direction) of the axles 13a to 13d of equations (1) to (4), the following equations (34) to (37) are obtained.

[ number 14]

Thus, by using the conversion variable e ₁ ～e ₄ To express equations (1) to (4) (equations describing the motion of the lateral vibrations (motion in the left-right direction) of the wheel shafts 13a to 13 d), whereby the rotation amount (angular displacement) ψ in the yaw direction of the wheel shafts 13a to 13d included in the equations of motion can be eliminated _w1 ～ψ _w4 。

When equations (22) to (25) are substituted into equations (11) and (12) (equations of motion describing the deflection of the bogies 12a and 12 b), the following equations (38) and (39) are obtained.

[ number 15]

Thus, by using the front-rear direction force T ₁ ～T ₄ To express the expression (11) and the expression (12) (the motion equation describing the deflection of the bogies 12a, 12 b), thereby eliminating the angular displacement ψ in the deflection direction of the wheel axles 13a to 13d included in the motion equation _w1 ～ψ _w4 Angular velocity ψ _w1 ·～ψ _w4 ·。

When formulae (26) to (29) are substituted into formulae (22) to (25), formulae (40) to (43) below are obtained.

[ number 16]

As described above, in the present embodiment, the equation of motion describing the lateral vibrations (movement in the left-right direction) of the axles 13a to 13d is expressed as the equations (34) to (37), and the equations of motion describing the deflections of the bogies 12a, 12b are expressed as the equations (38) and (39). Equations (34) to (39) are used to construct the state equation. The expressions (40) to (43) are ordinary differential equations. Conversion variable e as a solution to the ordinary differential equation ₁ ～e ₄ Can be obtained by using the fore-and-aft direction force T of the wheel shafts 13a to 13d ₁ ～T ₄ Is obtained by the value of (a). Here, the front-rear direction force T ₁ ～T ₄ The value of (2) is obtained from the past by a 1 st frequency adjustment unit 503 to be described laterThe time-series data of the measured values of the rearward force reduce the signal intensity of the low-frequency component generated by the running of the railway vehicle on the curved portion of the track.

The conversion variable e thus obtained ₁ ～e ₄ The actual values of (2) are given by the formulas (34) to (37). In addition, the front-rear direction force T of the wheel shafts 13a to 13d ₁ ～T ₄ The values of (3) and (39) are given. Here, the front-rear direction force T ₁ ～T ₄ The value (1) is obtained by reducing the signal intensity of the low frequency component generated by the running of the railway vehicle on the curved portion of the track from the time-series data of the measured value of the longitudinal force by the 1 st frequency adjustment unit 503 described later.

In the present embodiment, the variables represented by the following expression (44) are used as state variables, and equations of motion of expression (9), (10), (13) to (21), and (34) to (39) are used to construct equations of state.

[ number 17]

The storage unit 501 inputs and stores the state equation configured as described above, for example, based on an operation of the user interface 608 by the operator.

Next, the observation equation will be described.

In the present embodiment, acceleration in the left-right direction of the vehicle body 11, acceleration in the left-right direction of the trucks 12a, 12b, and acceleration in the left-right direction of the axles 13a to 13d are taken as observation variables. The observation variable is an observation variable filtered by a kalman filter described later. In this embodiment, the observation equation is configured using equations (34) to (37), equations (9), equations (10), and equations (15) (equations of motion describing lateral vibrations).

The storage unit 501 inputs and stores the observation equation thus configured, for example, based on an operation of the user interface 608 by an operator.

After the state equation and the observation equation are stored in the inspection apparatus 500 as described above, the data acquisition unit 502, the 1 st frequency adjustment unit 503, the state variable derivation unit 504, the 2 nd frequency adjustment unit 505, the track state derivation unit 506, and the output unit 507 are started. That is, the process based on the flowchart of fig. 7 starts after the state equation and the observation equation are stored in the inspection apparatus 500.

[ data acquisition section 502, S701]

The data acquisition unit 502 acquires time-series data of measured values of the front-rear force. The method for measuring the force in the front-rear direction is as described above. The data acquisition unit 502 can acquire time-series data of the measurement value of the front-rear force by communicating with an operation device for calculating the front-rear force using the measurement value of the strain gauge for measuring the front-rear force, for example. The data acquisition unit 502 does not acquire time-series data of measurement values of acceleration in the left-right direction of the vehicle body 11, time-series data of measurement values of acceleration in the left-right direction of the bogies 12a, 12b, and time-series data of measurement values of acceleration in the left-right direction of the axles 13a to 13 d.

[ 1 st frequency adjustment section 503, S702]

The 1 st frequency adjustment unit 503 reduces (preferably removes) the signal intensity of the low frequency component included in the time-series data of the measured value of the longitudinal force acquired by the data acquisition unit 502. The signal of the low frequency component is a signal which is not measured when the railway vehicle runs on a straight track with a curvature of 0 (zero), but is measured when the railway vehicle runs on a curved track. That is, the signal measured when the railway vehicle runs on the curved track can be regarded as a signal obtained by superimposing the signal of the low frequency component on the signal measured when the railway vehicle runs on the straight track having the curvature of 0 (zero).

The present inventors have studied a model in which an autoregressive model (AR) is corrected. The inventors of the present invention have also conceived to reduce the signal intensity of the low-frequency component included in the time-series data of the measured values of the front-rear force using the model. In the following description, the model developed by the present inventors is referred to as a modified autoregressive model. In contrast, a known autoregressive model is simply referred to as an autoregressive model. An example of the modified autoregressive model will be described below.

The value of time-series data of the physical quantity y at the time k (1. Ltoreq.k. Ltoreq.M) is set as y _k . M is a number of data indicating the time-series data of the physical quantity y up to which time point is included, and is set in advance. In the following description, time-series data of physical quantities will be simply referred to as data y as needed. Value y for data y _k The autoregressive model to be approximated is expressed by the following expression (45), for example. As shown in the expression (45), the autoregressive model is an actual value y of a physical quantity at a time k-l (1. Ltoreq.l.ltoreq.m) preceding the time k (m+1. Ltoreq.k.ltoreq.M) in the data y _k-l A predicted value y≡representing the physical quantity of the time k in the data y _k Is a formula of (2). In formula (45), y is _k Append the letter y _k 。

[ number 18]

(45) Where α is a coefficient of the autoregressive model. m is the value y for the data y for time k in the autoregressive model _k The number of values of the data y to be approximated is the value y of the data y at successive times k-1 to k-m preceding the time k _k-1 ～y _k-m Is a number of (c). M is an integer less than M. As m, 1500 can be used, for example.

Then, a least square method is used to determine a predicted value y≡for the physical quantity at time k based on an autoregressive model _k Approximated by the value y _k Is a conditional expression of (2). Predicted value y≡as physical quantity for making time k based on autoregressive model _k Approximated by the value y _k For example, a predicted value y≡of a physical quantity at time k based on an autoregressive model can be used _k And value y _k The condition for minimizing the square difference of (2). That is, in order to make the predicted value y≡of the physical quantity at time k based on the autoregressive model _k Approximated by the value y _k And the least squares method is used. The following formula (46) is usedPredicted value y≡of physical quantity at time k based on autoregressive model _k And value y _k The least square difference of (b) is a conditional expression.

[ number 19]

The following relationship of expression (47) is established according to expression (46).

[ number 20]

The following expression (48) is obtained by deforming (matrix expression) expression (47).

[ number 21]

(48) R in the formula _jl Is a value called the autocorrelation of the data y, and is a value defined by the following expression (49). The value of j-l in this case is referred to as the time difference.

[ number 22]

Based on the expression (48), the following expression (50) is considered. (50) The expression is based on the predicted value y≡of the physical quantity at the time k based on the autoregressive model _k And the predicted value y _k The value y of the physical quantity at the corresponding time k _k An equation derived from the condition that the error between them is minimized. (50) The formula is called You Er-Wacker (Yule-Walker) equation. The expression (50) is a linear equation in which a vector composed of coefficients of the autoregressive model is used as a variable vector. (50) The constant vector on the left side in the expression is a vector having as a component the autocorrelation of data y with a time difference from 1 to m. In the following description, the following description will be given as needed 50 The constant vector on the left in the equation is called the autocorrelation vector. The coefficient matrix on the right in the expression (50) is a matrix having as components the autocorrelation of data y with a time difference from 0 to m-1. In the following description, the coefficient matrix on the right side in the expression (50) is referred to as an autocorrelation matrix as necessary.

[ number 23]

In addition, the autocorrelation matrix (represented by R _jl The m×m matrix configured) is expressed as an autocorrelation matrix R as expressed by the following expression (51).

[ number 24]

In general, when coefficients of an autoregressive model are obtained, a method of solving (50) expression for the coefficient α is used. In the expression (50), the predicted value y≡of the physical quantity at the time k derived by the autoregressive model is calculated _k The value y of the physical quantity as close as possible to the time k _k The coefficient alpha is derived by way of (a). Therefore, the frequency characteristic of the autoregressive model includes the value y of the data y at each time _k A plurality of frequency components are included.

Accordingly, the present inventors focused on the autocorrelation matrix R multiplied by the coefficient α of the autoregressive model, and conducted intensive studies. As a result, the present inventors have found that the influence of the high-frequency component included in the data y can be reduced by using a part of the eigenvalues of the autocorrelation matrix R. That is, the present inventors found that the autocorrelation matrix R can be rewritten so that the low-frequency component is emphasized.

A specific example of this will be described below.

Singular value decomposition is performed on the autocorrelation matrix R. The elements of the autocorrelation matrix R are symmetrical. Therefore, when the singular value decomposition is performed on the autocorrelation matrix R, the product of the orthogonal matrix U, the diagonal matrix Σ, and the transpose matrix of the orthogonal matrix U is obtained as in the following expression (52).

[ number 25]

R＝U∑U ^T …(52)

As shown in the following expression (53), the diagonal matrix Σ of expression (52) is a matrix whose diagonal component is the eigenvalue of the autocorrelation matrix R. Setting the diagonal component of the diagonal matrix sigma to sigma ₁₁ 、σ ₂₂ 、……、σ _mm . The orthogonal matrix U is a matrix in which each column component vector is a feature vector of the autocorrelation matrix R. Let the column component vector of the orthogonal matrix U be U ₁ 、u ₂ 、……、u _m . The autocorrelation matrix R is relative to the eigenvector u _j Characteristic value of sigma _jj Such correspondence relation. The eigenvalue of the autocorrelation matrix R is a predicted value y≡reflecting the physical quantity at time k based on the autoregressive model _k A variable of the intensity of the component of each frequency included in the time waveform.

[ number 26]

A diagonal component of the diagonal matrix sigma, i.e. sigma, obtained from the result of the singular value decomposition of the autocorrelation matrix R ₁₁ 、σ ₂₂ 、……、σ _mm The values of (2) are set in descending order to simplify the expression of the expression. The matrix R' is defined as the following expression (54) using s eigenvalues from the largest eigenvalue among the eigenvalues of the autocorrelation matrix R shown in expression (53). s is a number of 1 or more and less than m. In the present embodiment, s is predetermined. The matrix R' is a matrix obtained by approximating the autocorrelation matrix R with s eigenvalues among the eigenvalues of the autocorrelation matrix R.

[ number 27]

(54) Matrix U in _s Is formed by s columns from left of (52) orthogonal matrix UThe component vectors (eigenvectors corresponding to the eigenvalues used) constitute an mxs matrix. I.e. matrix U _s Is a partial matrix formed by cutting out the left m×s elements from the orthogonal matrix U. In addition, U in the formula (54) _s ^T Is U _s Is a transposed matrix of (a). U (U) _s ^T Is a matrix U consisting of (52) ^T S x m matrix of s row component vectors from the upper side. (54) Matrix Σ in _s Is an sxs matrix composed of s columns from the left side and s rows from the upper side of the diagonal matrix Σ of the expression (52). That is, the matrix Σ _s Is a partial matrix formed by cutting the upper left sx elements from the diagonal matrix Σ.

If matrix sigma is represented by matrix elements _s Matrix U _s The expression (55) below is assumed.

[ number 28]

By using the matrix R' instead of the autocorrelation matrix R, the relational expression of expression (50) is rewritten as expression (56) below.

[ number 29]

By deforming the expression (56), the following expression (57) is obtained as an expression for obtaining the coefficient α. Using the coefficient α obtained by the expression (57), a predicted value y≡of the physical quantity at the time k is calculated from the expression (45) _k Is a "modified autoregressive model".

[ number type 30]

Here, to divide the diagonal component of the diagonal matrix Σ, i.e., σ ₁₁ 、σ ₂₂ 、……、σ _mm The case where the values of (2) are in descending order is described as an example. However, the diagonal components of the diagonal matrix Σ need not be in descending order during the calculation of the coefficient α. In this case, matrix U _s Instead of the partial matrix formed by cutting the left m×s elements from the orthogonal matrix U, the partial matrix formed by cutting the column component vector (eigenvector) corresponding to the eigenvalue used is cut. Furthermore, the matrix Σ _s Instead of a local matrix formed by cutting the upper left sx elements from the diagonal matrix Σ, a local matrix is cut so that the eigenvalue used for determining the coefficient of the modified autoregressive model is set as the diagonal component.

(57) The equation is an equation used in determining coefficients of the modified autoregressive model. (57) Matrix U _s The local matrix of the orthogonal matrix U obtained by singular value decomposition of the autocorrelation matrix R is a matrix in which eigenvectors corresponding to eigenvalues used for coefficient determination of the modified autoregressive model are set as column component vectors (matrix 3). Furthermore, (57) matrix Σ _s The local matrix is a diagonal matrix obtained by singular value decomposition of the autocorrelation matrix R, and is a matrix (the 2 nd matrix) having, as diagonal components, eigenvalues used for coefficient determination of the modified autoregressive model. (57) Matrix U _s Σ _s U _s ^T Is based on the matrix Σ _s Sum matrix U _s Derived matrix (matrix 1).

The coefficient α of the corrected autoregressive model is obtained by calculating the right side of the expression (57). In the above, an example of a method for deriving the coefficient α of the modified autoregressive model is described. Here, for the sake of visual understanding, the method of deriving the coefficients of the autoregressive model that is the basis of the corrected autoregressive model is set as the predicted value y ζ of the physical quantity at the time k _k A method using a least squares method. However, in general, a method of defining an autoregressive model using a concept of a probability process and deriving coefficients thereof is known. In this case, the autocorrelation is represented by the autocorrelation of the probabilistic process (overall). The autocorrelation of the probability process is represented as a function of the time difference. Thus, the numbers in the present embodimentThe autocorrelation of y may be replaced with a value calculated by another calculation formula as long as the autocorrelation of the probability process is approximated. For example, R ₂₂ ～R _mm Is an autocorrelation with a time difference of 0 (zero), but they can also be replaced by R ₁₁ 。

For example, the number s of eigenvalues extracted from the autocorrelation matrix R shown in expression (53) can be determined from the distribution of eigenvalues of the autocorrelation matrix R.

Here, the physical quantity in the above description of the modified autoregressive model is the front-rear direction force. The value of the longitudinal force varies according to the state of the railway vehicle or the like.

Therefore, first, the railway vehicle is caused to travel on the rail 16, and data y relating to the measured value of the longitudinal force is obtained. For each of the obtained data y, the autocorrelation matrix R is obtained using the expression (49) and the expression (51). The eigenvalues of the autocorrelation matrix R are obtained by performing singular value decomposition represented by expression (52) on the autocorrelation matrix R. Fig. 8 is a diagram showing an example of the distribution of eigenvalues of the autocorrelation matrix R. In fig. 8, the force T in the forward-backward direction with the wheel shaft 13a will be applied ₁ The eigenvalue sigma obtained by singular value decomposition of the autocorrelation matrix R to which the data of the measured value y of (a) are respectively related ₁₁ ～σ _mm Rearranging in ascending order and drawing. The horizontal axis of fig. 8 is an index of the eigenvalues, and the vertical axis is a value of the eigenvalues.

In the example shown in fig. 8, there is one feature value having a significantly higher value than others. Further, although the above-described feature value having a significantly high value is not reached, there are two feature values which have a relatively large value compared with others and are not regarded as 0 (zero). In this case, for example, 2 or 3 can be used as the number s of eigenvalues extracted from the autocorrelation matrix R shown in expression (53). Whichever is employed, the results do not differ significantly. The number of characteristic values having significantly higher values than others may be changed depending on the structure of the railway vehicle, the structure of the track, and the like. Therefore, the number s of eigenvalues extracted from the autocorrelation matrix R is not limited to 1 or more.

Every time the data acquisition unit 502 acquires the value y of time k of time series data of the measurement value y of the longitudinal force at a predetermined sampling period _k The 1 st frequency adjustment unit 503 performs the following processing.

First, the 1 st frequency adjustment unit 503 generates the autocorrelation matrix R using the expressions (49) and (51) based on time-series data of the measured value y of the longitudinal force and the preset number M, m.

Next, the 1 st frequency adjustment unit 503 performs singular value decomposition on the autocorrelation matrix R to derive (52) an orthogonal matrix U and a diagonal matrix Σ, and derives a eigenvalue σ of the autocorrelation matrix R from the diagonal matrix Σ ₁₁ ～σ _mm 。

Next, the 1 st frequency adjustment unit 503 sets a plurality of eigenvalues σ of the autocorrelation matrix R ₁₁ ～σ _mm In s eigenvalues from the largest eigenvalue ₁₁ ～σ _ss The eigenvalue of the autocorrelation matrix R used when the coefficient α of the modified autoregressive model is found is selected.

Next, the 1 st frequency adjustment unit 503 is based on the time-series data of the measured value y of the longitudinal force and the characteristic value σ ₁₁ ～σ _ss And an orthogonal matrix U obtained by singular value decomposition of the autocorrelation matrix R, and the coefficient alpha of the modified autoregressive model is determined by using the formula (57).

Then, the 1 st frequency adjustment unit 503 derives the predicted value y Σ of the time k of the time series data of the measured value y of the front-rear direction force by the expression (45) based on the coefficient α of the correction autoregressive model and the time series data of the measured value y of the front-rear direction force _k . Predicted value y-S of force in front-back direction _k The time-series data of (2) is obtained by extracting the low-frequency component included in the time-series data of the measurement value y of the force in the front-rear direction.

Fig. 9 is a diagram showing an example of time-series data (measured value) of measured values of the force in the front-rear direction and time-series data (calculated value) of predicted values of the force in the front-rear direction. In the present embodiment, 4 longitudinal forces T are obtained ₁ ～T ₄ Is measured by the above method. Namely, in the front-rear directionThe force gives 4 data y. The measured values and calculated values for each of these 4 data y are shown in fig. 9. The horizontal axis in fig. 9 represents the elapsed time (seconds) from the reference time point when the reference time point is set to 0 (zero), and represents the longitudinal force T ₁ ～T ₄ Measurement time and calculation time of (a). The vertical axis is the force T in the front-back direction ₁ ～T ₄ (Nm)。

In fig. 9, the wheel shaft 13a has a force T in the front-rear direction ₁ The calculated value of (2) is biased approximately between 15 seconds and 35 seconds. Namely, the force T in the front-rear direction of the wheel shaft 13a ₁ The calculated value of (2) shows a value greater than the other time at about 15 seconds to 35 seconds. This period corresponds to the period during which the axle 13a passes through the curved track. Force T in the front-rear direction with respect to the wheel shaft 13b ₂ Calculated value of (2), the front-rear direction force T of the wheel shaft 13c ₃ Calculated value of (2) and the front-rear direction force T of the wheel shaft 13d ₄ Is also in accordance with the front-rear direction force T of the wheel shaft 13a ₁ Similarly, the offset is generated during the period in which the axles 13b, 13c, 13d pass through the curved track.

Thus, in FIG. 9, if the force T is in the front-rear direction from the wheel shafts 13a to 13d ₁ ～T ₄ By removing the calculated value from the measured value of (2), the front-rear direction force T can be removed ₁ ～T ₄ Low frequency components generated by the wheel axles 13a to 13d passing through a curved track. That is, in FIG. 9, if the force T is in the front-rear direction from the wheel shafts 13a to 13d ₁ ～T ₄ If the calculated value is removed from the measured value of (a), the wheel axles 13a to 13d pass through the curved track, and the force T in the front-rear direction is calculated ₁ ～T ₄ The same longitudinal force as in the case where the wheel shafts 13a to 13d pass through the linear rail can be obtained.

Therefore, the 1 st frequency adjustment unit 503 measures the value y of force in the front-rear direction _k Subtracting a predicted value y-a of the front-rear force from time-series data (data y) _k Is provided). In the following description, the measured value y of the force in the front-rear direction will be measured as needed _k Subtracting a predicted value y-a of the front-rear force from time-series data (data y) _k Time series data obtained from the time series data of (a) is called the time of the high frequency component of the front-rear direction force Inter-sequence data. The value of each sampling time of the time-series data of the high-frequency component of the front-rear force is referred to as a value of the high-frequency component of the front-rear force, if necessary.

Fig. 10 is a diagram showing an example of time-series data of high-frequency components of the force in the front-rear direction. The vertical axis of FIG. 10 shows the front-rear direction force T ₁ 、T ₂ 、T ₃ 、T ₄ Time-series data of high-frequency components of (a) are provided. Namely, the longitudinal force T shown in the vertical axis of FIG. 10 ₁ 、T ₂ 、T ₃ 、T ₄ By the forces T in the front-rear direction from the axles 13a, 13b, 13c, 13d shown in FIG. 9 ₁ 、T ₂ 、T ₃ 、T ₄ The calculated value is subtracted from the measured value of (c). Note that, in fig. 10, the horizontal axis is the elapsed time (seconds) from the reference time point when the reference time point is set to 0 (zero), and the horizontal axis is the same as the horizontal axis in fig. 9, and indicates the longitudinal force T ₁ ～T ₄ Measurement time and calculation time of (a).

The 1 st frequency adjusting unit 503 derives the longitudinal force T as described above ₁ ～T ₄ Time-series data of high-frequency components of (a) are provided.

[ State variable derivation section 504, S703]

The state variable deriving unit 504 determines the estimated value of the state variable represented by expression (44) by a kalman filter, using the observation equation stored in the storage unit 501 and the state equation stored in the storage unit 501. At this time, the state variable deriving unit 504 uses the longitudinal force T generated by the 1 st frequency adjusting unit 503 ₁ ～T ₄ Time-series data of high-frequency components of (a) are provided. In the present embodiment, at least the longitudinal force T is obtained without using time-series data of the measurement value of the acceleration in the left-right direction of the vehicle body 11, time-series data of the measurement value of the acceleration in the left-right direction of the bogies 12a, 12b, and time-series data of the measurement value of the acceleration in the left-right direction of the axles 13a to 13d when determining the estimated value of the state variable ₁ ～T ₄ Time-series data during the measurement values of (a) are obtained.

The kalman filter is one of the methods for data assimilation. That is, the kalman filter is an example of a method of determining the estimated value of an unobserved variable (state variable) so that the difference between the measured value and the estimated value of the observable variable (observed variable) becomes small (minimum). The state variable deriving unit 504 obtains a kalman gain in which the difference between the measured value and the estimated value of the observed variable becomes small (minimum), and obtains an estimated value of an unobserved variable (state variable) at this time. The kalman filter uses the following equation (58) for observation and the following equation (59) for state.

Y＝HX+V …(58)

X·＝ΦX+W …(59)

In expression (58), Y is a vector that holds the measured value of the observed variable. H is the observation model. X is a vector that holds state variables. V is observation noise. In the expression (59), x·represents the time derivative of X. Φ is a linear model. W is system noise. The kalman filter itself can be realized by a known technique, and thus a detailed description thereof will be omitted.

In the technique described in patent document 1, measured values (measured values of acceleration in the left-right direction of the vehicle body 11, measured values of acceleration in the left-right direction of the bogies 12a, 12b, and measured values of acceleration in the left-right direction of the axles 13a to 13 d) are directly used as values given as measured values of observation variables. In contrast, in the present embodiment, as described in the section [ 1 st concept ], a value given as a measurement value that is originally an observation variable is given not a measurement value but a predetermined constant value at the time of data assimilation. In the present embodiment, the average value of time-series data of acceleration is set to 0 (zero), and all constant values given as observation variables are set to 0 (zero). Therefore, in the present embodiment, the state variable deriving unit 504 derives the estimated value of the state variable so that the error of the estimated value of the observed variable with respect to the constant value (here, 0 (zero)) becomes minimum or the expected value of the error becomes minimum when data assimilating is performed.

The state variable deriving unit 504 determines the estimated value of the state variable represented by expression (44) at a predetermined sampling period, thereby generating time-series data of the estimated value of the state variable represented by expression (44).

[ frequency adjustment section 505, S704]

If the signal intensity of the low frequency component included in the time-series data of the measured value of the longitudinal force is not sufficiently removed by the 1 st frequency adjustment unit 503, there is a possibility that a signal of the low frequency component due to the running of the railway vehicle on the curved track remains in the time-series data of the estimated value of the state variable generated by the state variable derivation unit 504. Therefore, the 2 nd frequency adjustment unit 505 reduces (preferably removes) the signal strength of the low frequency component included in the time-series data of the estimated value of the state variable generated by the state variable derivation unit 504. In addition, when the number s of eigenvalues extracted from the autocorrelation matrix R shown in expression (53) can be determined so that the signal intensity of the low-frequency component included in the time-series data of the measured values of the front-rear force can be sufficiently removed by the 1 st frequency adjustment unit 503, the processing by the 2 nd frequency adjustment unit 505 is not required.

In the present embodiment, the 2 nd frequency adjustment unit 505 uses a modified autoregressive model to reduce the signal strength of the low frequency component included in the time-series data of the estimated value of the state variable, as in the 1 st frequency adjustment unit 503.

The 2 nd frequency adjustment unit 505 performs the following processing for each state variable at a predetermined sampling period.

Here, the physical quantity in the above description of the modified autoregressive model becomes a state variable. That is, the data y of the state variable is time-series data of the estimated value of the state variable generated by the state variable deriving unit 504. The estimated values of the state variables all vary according to the state of the railway vehicle.

First, the 2 nd frequency adjustment unit 505 generates the autocorrelation matrix R using the expression (49) and the expression (51) based on the data y of the estimated value of the state variable and the preset number M, m.

Then, the 2 nd frequency adjustment unit 505 performs singular value decomposition on the autocorrelation matrix R to derive [ ]52 An orthogonal matrix U and a diagonal matrix sigma, and deriving the eigenvalue sigma of the autocorrelation matrix R from the diagonal matrix sigma ₁₁ ～σ _mm 。

Next, the 2 nd frequency adjustment unit 505 sets a plurality of eigenvalues σ of the autocorrelation matrix R ₁₁ ～σ _mm S eigenvalues σ11 to σss from the largest eigenvalue are selected as eigenvalues of the autocorrelation matrix R to be used when obtaining the coefficient α of the modified autoregressive model. S is preset for each state variable. For example, the state in which the railway vehicle is driven on the track 16 is obtained, and the estimated value data y of each state variable is obtained as described above. Then, the 2 nd frequency adjustment unit 505 creates a distribution of eigenvalues of the autocorrelation matrix R for each state variable independently. The 2 nd frequency adjustment unit 505 determines the number s of eigenvalues extracted from the autocorrelation matrix R shown in expression (53) for each state variable based on the distribution of eigenvalues of the autocorrelation matrix R.

Next, the 2 nd frequency adjustment unit 505 calculates the feature value σ and the data y based on the estimated value of the state variable ₁₁ ～σ _ss And an orthogonal matrix U obtained by singular value decomposition of the autocorrelation matrix R, and the coefficient alpha of the modified autoregressive model is determined by using the formula (57).

Then, the 2 nd frequency adjustment unit 505 derives the predicted value y ζ of the time k of the data y of the estimated value of the state variable by the expression (45) based on the coefficient α of the correction autoregressive model and the data y of the estimated value of the state variable _k . Predicted value y-A of state variable _k The time-series data of (2) is obtained by extracting a low-frequency component included in the data y of the estimated value of the state variable.

Then, the 2 nd frequency adjustment unit 505 subtracts the predicted value y ζ of the state variable from the data y of the predicted value of the state variable _k Is provided). In the following description, the predicted value y≡of the state variable is subtracted from the data y of the predicted value of the state variable as needed _k The value of each sampling time of the time series data obtained from the time series data of (a) is referred to as the value of the high frequency component of the state variable.

Track state deriving unit 506, S705

When equations (22) to (25) are substituted into equations of motion describing the deflection of the axles 13a to 13d of equations (5) to (8), the following equations (60) to (63) are obtained.

[ number 31]

In the present embodiment, the force T representing the longitudinal direction is determined as shown in the formulae (60) to (63) ₁ ～T ₄ Through irregularities y at positions corresponding to the wheel shafts 13a to 13d _R1 ～y _R4 A relational expression of the relationship between them.

The track state deriving unit 506 calculates the rotation amount (angular displacement) ψ in the yaw direction of the wheel shafts 13a to 13d from the expressions (30) to (33) _w1 ～ψ _w4 Is a speculative value of (c). Then, the track state deriving unit 506 calculates the rotation amount (angular displacement) ψ in the yaw direction of the wheel shafts 13a to 13d _w1 ～ψ _w4 The estimated value of (2), the value of the high frequency component of the state variable generated by the 2 nd frequency adjustment unit 505, and the longitudinal force T generated by the 1 st frequency adjustment unit 503 ₁ ～T ₄ The high frequency component value of (3) is given to equations (60) to (63), thereby calculating the end irregularity y at the positions of the wheel shafts 13a to 13d _R1 ～y _R4 . The state variable used herein is the displacement y of the bogies 12a to 12b in the left-right direction _t1 ～y _t2 Bogies 12a to 12b velocity y in the left-right direction _t1 ·～y _t2 Left-right displacement y of the axles 13 a-13 d _w1 ～y _w4 And the speed y of the axles 13 a-13 d in the left-right direction _w1 ·～y _w4 And (3) the process. The track state deriving unit 506 performs the above-described passing-end irregularity amount y at a predetermined sampling period _R1 ～y _R4 To thereby obtain the open-end irregularity y _R1 ～y _R4 Is provided).

Then, the track state deriving unit 506 derives the track state from the end irregularity y _R1 ～y _R4 To calculate the final open-end irregularity y _R . For example, the track state deriving unit 506 makes the leading end irregularity amount y _R2 ～y _R4 Phase and end-of-line irregularity y of time-series data of (2) _R1 Is identical in phase with the time series data of the same. That is, the track state deriving unit 506 calculates the delay time of the moment when the wheel axle 13b to 13d passes through a certain position with respect to the moment when the wheel axle 13a passes through the position, based on the distance in the front-rear direction between the wheel axle 13a and the wheel axles 13b to 13d and the speed of the railway vehicle. The track state deriving unit 506 derives the amount y of the end irregularity _R2 ～y _R4 Is phase-shifted by the delay time.

The track state deriving unit 506 calculates the common-end irregularity y after the phase matching _R1 ～y _R4 Arithmetic mean of the sum of the values of the same sampling instants as the final end-of-line irregularity y of that sampling instant _R . The track state deriving unit 506 performs such calculation at each sampling timing to obtain the final passing-end irregularity y _R Is provided). Due to the irregular amount y of the leading end _R2 ～y _R4 Phase and end of line irregularity y _R1 The phase of (a) is uniform, so that the irregularity y at the through end can be made _R1 ～y _R4 The co-existing interference factors cancel out in the time series data of (a).

The track state deriving unit 506 may also be configured to adjust the phase to the common-end irregularity y _R1 ～y _R4 The moving averages are taken (i.e., by low pass filters) respectively,and according to the end irregularity y obtained by the moving average _R1 ～y _R4 To calculate the final open-end irregularity y _R 。

The track state deriving unit 506 may calculate the common-end irregularity y after the phase is matched _R1 ～y _R4 Arithmetic mean of two values other than maximum and minimum of the values at the same sampling time of (a), as the final end-of-line irregularity y _R 。

The inspection device 500 uses time-series data of the measured values of the longitudinal force at each sampling time acquired by the data acquisition unit 502 during the travel of the railway vehicle in the travel section of the derivation target of the passing irregularity amount, and executes the processing of the 1 st frequency adjustment unit 503, the state variable derivation unit 504, the 2 nd frequency adjustment unit 505, and the track state derivation unit 506.

In this way, the track state deriving unit 506 can obtain the passing end irregularity y at each sampling time during which the railway vehicle travels in the travel section of the deriving target of the passing end irregularity _R . The track state deriving unit 506 calculates the running position of the railway vehicle at each sampling time based on, for example, the running speed of the railway vehicle and the elapsed time from the start of the running of the railway vehicle. The running position of the railway vehicle can be set to, for example, the position of the wheel shaft 13 a. The track state deriving unit 506 derives the end irregularity y at each sampling timing _R And the running position of the railway vehicle at each sampling time, and deriving the final passing-end irregularity y at each running position of the railway vehicle _R 。

The track state deriving unit 506 does not necessarily have to calculate the running position of the railway vehicle at each sampling time as described above. For example, the track state deriving unit 506 may calculate the running position of the railway vehicle at each sampling time by using GPS (Global Positioning System: global positioning system).

Output section 507, S706

The output unit 507 outputs the final end irregularity y calculated by the track state deriving unit 506 _R Is a piece of information of (a). At this time, the final end irregularity y _R When the value is larger than the preset value, the output unit 507 may output information indicating that the track 16 is abnormal. The output mode may be at least one of display on a computer display, transmission to an external device, and storage on an internal or external storage medium.

[ summary ]

As described above, in the present embodiment, the inspection device 500 applies the longitudinal force T ₁ ～T ₄ Measured value of (2), and conversion variable e ₁ ～e ₄ Is applied to the Kalman filter to derive the state variables At this time, at the time of data assimilation, a predetermined constant value (for example, 0 (zero)) is used as a value (acceleration in the left-right direction of the vehicle body 11, the trucks 12a, 12b, and the axles 13a to 13 d) which is originally given as a measurement value of an observation variable. Next, the inspection apparatus 500 uses the rotation amount (angular displacement) ψ in the yaw direction of the bogies 12a, 12b included in the above state variables _t1 ～ψ _t2 And a conversion variable e ₁ ～e ₄ Derives the rotation amount (angular displacement) ψ in the yaw direction of the axles 13 a-13 d _w1 ～ψ _w4 . Next, the inspection device 500 substitutes the rotation amounts (angular displacements) ψ in the deflection directions of the wheel shafts 13a to 13d into the equation of motion describing the deflection of the wheel shafts 13a to 13d _w1 ～ψ _w4 The state variable, and the front-rear force T ₁ ～T ₄ Deriving the amount y of end irregularities at the positions of the axles 13 a-13 d _R1 ～y _R4 . Then, the inspection apparatus 500 performs inspection based on the through-end irregularity y _R1 ～y _R4 Deriving final open-end irregularity y _R . Therefore, the end irregularities can be introduced without greatly reducing the accuracy without using the measured values of the acceleration in the lateral direction of the vehicle body 11, the bogies 12a, 12b, and the axles 13a to 13dQuantity y _R1 ～y _R4 (final open-end irregularity y _R ). Thus, the lead-out end irregularity y can be reduced _R1 ～y _R4 (final open-end irregularity y _R ) The number of sensors used.

In the present embodiment, the inspection apparatus 500 generates the autocorrelation matrix R from the time-series data of the measurement value y of the front-rear force, and determines the coefficient α of the modified autoregressive model that approximates the time-series data of the measurement value y of the front-rear force using s eigenvalues from the largest eigenvalue among eigenvalues obtained by singular value decomposition of the autocorrelation matrix R. Therefore, the coefficient α can be determined such that the signal of the low frequency component and the signal of the high frequency component contained in the time-series data of the measurement value y of the force in the front-rear direction remain. The inspection apparatus 500 calculates a predicted value y≡of the force in the front-rear direction at time k by adding time-series data of the measured value y of the force in the front-rear direction at time k-l (1+.l.ltoreq.m) before time k to the corrected autoregressive model in which the coefficient α is thus determined _k . Therefore, the signal of the low frequency component generated by the rolling stock traveling on the curved track can be reduced from the time-series data of the measured value y of the front-rear force without assuming the cutoff frequency in advance. Then, the inspection apparatus 500 reduces the front-rear direction force T in this way ₁ ～T ₄ Signal intensity of low frequency component contained in time-series data of measured values of (2) to generate longitudinal force T ₁ ～T ₄ Time-series data of high-frequency components of (a) are provided. The inspection device 500 applies the longitudinal force T ₁ ～T ₄ Time-series data of high-frequency components of (a) are imparted to the front-rear direction force T ₁ ～T ₄ Through irregularities y at positions corresponding to the wheel shafts 13a to 13d _R1 ～y _R4 From the relation, the end irregularity y at the positions of the wheel shafts 13a to 13d is calculated _R1 ～y _R4 . The relational expression is a formula based on a motion equation describing the motion of the railway vehicle when traveling on a straight track (i.e., a formula that does not include the radius of curvature R of the track 16 (rail)). Thus, the rolling stock is based on a straight railEquation of motion describing motion during on-road travel, the end irregularity y of a curved track can be detected without using a special measuring device _R1 ～y _R4 (final open-end irregularity y _R )。

Modification example

In the present embodiment, a predetermined constant value is given as a value given as a measurement value which is originally used as an observation variable in data assimilation. The constant value is not limited to 0 (zero). For example, a railway vehicle having the inspection device 500 mounted thereon or a railway vehicle equivalent to the railway vehicle (a railway vehicle having the same structure as the railway vehicle) may be obtained, with respect to the passing-end irregularity y _R1 ～y _R4 (final open-end irregularity y _R ) The average value of the time-series data of the measured values of the acceleration in the left-right direction of the vehicle body 11, the time-series data of the measured values of the acceleration in the left-right direction of the bogies 12a, 12b, and the time-series data of the measured values of the acceleration in the left-right direction of the axles 13a to 13d when the vehicle is traveling on the track 16 to be derived is used as a constant value. Further, using these measured values, the acceleration y≡in the left-right direction of the vehicle body 11 is derived by the above-described correction autoregressive model _k Time-series data of predicted values of (a), acceleration y≡in the left-right direction of the bogies 12a, 12b _k Time-series data of predicted values of (a), and predicted values y≡of accelerations in the left-right directions of the wheel shafts 13a to 13d _k Is provided). These average values can then also be used as constant values. In this case, although the acceleration is measured, the measurement may be performed once for each railway vehicle and each rail 16, and the longitudinal force T of the wheel axles 13a to 13d may not be obtained when deriving the state variables ₁ ～T ₄ Acceleration measurement value during the measurement value period of (a).

In this embodiment, a case where a modified autoregressive model is used will be described as an example. However, it is not necessarily required to use a modified autoregressive model to reduce the signal of the low frequency component generated by the running of the railway vehicle on the curved track from the time-series data of the measured value y of the front-rear direction force. For example, in the case where the frequency band generated by the rolling stock traveling on the curved track can be specified, a high-pass filter may be used to reduce the signal of the low-frequency component generated by the rolling stock traveling on the curved track from the time-series data of the measurement value y of the force in the front-rear direction. In the case where the track on which the railway vehicle is traveling is a linear track (ideal with a curvature of 0 (zero)) or a track that is a linear track in design but has a curvature that does not affect the estimation accuracy of the passing-end irregularity, the processing of the 1 st frequency adjusting unit 503 and the 2 nd frequency adjusting unit 505 is not required.

In the present embodiment, a case where the wheel axis to be the reference for the phase matching is the wheel axis 13a will be described as an example. However, the reference wheel shaft may be a wheel shaft 13b, 13c or 13d other than the wheel shaft 13 a.

In the present embodiment, a case where a kalman filter is used will be described as an example. However, a kalman filter is not necessarily required as long as a filter (i.e., a filter for performing data assimilation) that derives the estimated value of the state variable so that the error of the estimated value of the observed variable with respect to the constant value is minimized or the expected value of the error is minimized is used. For example, a particle filter may also be used. As an error of the estimated value of the observed variable with respect to the constant value, for example, a square error between the estimated value of the observed variable and the constant value is cited.

In the present embodiment, a case where the through-end irregularity is derived is described as an example. However, as the information reflecting the state of the track 16, it is only necessary to derive information reflecting the track irregularity (defect in the appearance of the track 16), and it is not necessary to derive the end irregularity. For example, the following expressions (64) to (67) may be calculated based on or instead of the passing irregularity, so as to derive the lateral pressure (the stress in the left-right direction between the wheels and the rail) generated when the railway vehicle runs on the linear rail. Wherein Q is ₁ 、Q ₂ 、Q ₃ 、Q ₄ The lateral pressure of the wheels 14a, 14b, 14c, 14d, respectively. f (f) ₃ Indicating spin creep coefficient.

[ number 32]

/>

In the present embodiment, a case where a state variable indicating the state of the vehicle body 11 is included is described as an example. However, the vehicle body 11 is a portion to which vibration generated by the acting force (creep force) between the wheels 14a to 14d and the rail 16 eventually propagates. Thus, for example, when it is determined that the influence of the propagation is small in the vehicle body 11, the state variable indicating the state of the vehicle body 11 may not be included. In this case, the equations (15) to (17) (equations of motion describing lateral vibration, deflection, and roll of the vehicle body 11) and the equations (18) and (19) (equations of motion describing deflection of the deflection damper disposed in the bogie 12a and the deflection damper disposed in the bogie 12 b) among the equations (1) to (21) are not required. In the equations of equations (1) to (21), the state quantity related to the vehicle body (the state quantity including the subscript b) and the value within { } including the state quantity related to the vehicle body (the state quantity including the subscript b) are calculated (for example, the left 3 rd item of equation (21)Set to 0 (zero).

In the present embodiment, the description has been made taking, as an example, a case where the bogies 12a, 12b are shaftless bogies. However, the bogies 12a, 12b are not limited to the shaftless bogies. The equation of motion can be appropriately rewritten according to the constituent elements of the railway vehicle, the forces received by the railway vehicle, the direction of motion of the railway vehicle, and the like. That is, the equation of motion is not limited to the equation of motion illustrated in the present embodiment. When the equation of motion indicates that the railway vehicle receives an external force independent of the state variable, the equation of state includes a term indicating the external force.

(embodiment 2)

Next, embodiment 2 will be described. In embodiment 1, the following description will be given by way of example: at the time of data assimilation, values (acceleration in the left-right direction of the vehicle body 11, acceleration in the left-right direction of the trucks 12a, 12b, and acceleration in the left-right direction of the axles 13a to 13 d) which are originally given as measurement values of observation variables are set to a constant value (0 (zero)), and a filter (kalman filter) for data assimilation is used to derive a state variable. In contrast, in the present embodiment, a case will be described in which a state variable is derived without data assimilation. As described above, this embodiment is mainly different from embodiment 1 in the method of deriving a state variable (the function of the state variable deriving unit 504). Therefore, in the description of the present embodiment, the same reference numerals and the like as those given in fig. 1 to 10 are given to the same parts as those of embodiment 1, and detailed description thereof is omitted.

In the present embodiment, the storage unit 501 stores not the equation of state ((58) and the observation equation ((59)) but the following equation of motion (68).

X·＝cΦX …(68)

(68) The expression is an example of an expression in which the state variable represented by expression (44) is expressed by equations of motion from expression (9), (10), (13) to expression (21), and (34) to expression (39) (expression in expression (68), c is 1), and the change in time of the state variable is smaller than that of the expression. Specifically, expression (68) is an expression obtained by multiplying the term of the first-order time derivative (x·) of the state variable by the forgetting coefficient (forgetting factor) c by the term connected with the equal sign, among the expressions obtained by using the equations of motion expressed by expressions (9), (10), (13) to (21) and (34) to (39) using the state variable shown in expression (44). That is, expression (68) is an expression in which the forgetting coefficient c is introduced into the state equation of expression (59) to make the system noise W0 (zero).

The forgetting coefficient c is a predetermined value, and is (theoretically) a value (0<c. Ltoreq.1) exceeding 0 and 1 or less. The forgetting coefficient c functions so that the smaller the value thereof, the more past observations are forgotten. In the expression (68), the smaller the value of the forgetting coefficient c is, the smaller the influence of the measured value of the front-rear direction force on the estimated value (solution) of the state variable is. Therefore, from the viewpoint of accurately obtaining the estimated value (solution) of the state variable, the value of the forgetting coefficient c is preferably close to 1. On the other hand, when the value of the forgetting coefficient c is excessively large, the possibility of the estimated value (solution) of the state variable diverging becomes high. In this embodiment, the expression (68) is directly solved without using a filter for data assimilation. Therefore, it is necessary to suppress the estimated value (solution) divergence of the state variable. From the above point of view, the value of the forgetting coefficient c is determined. The forgetting coefficient c is, for example, most preferably 1.0 among values exceeding 0.0 and not more than 1.0 (0.0 < c.ltoreq.1.0), preferably 0.90 or more and not more than 1.0 (0.90.ltoreq.c.ltoreq.1.0), more preferably 0.95 or more and not more than 1.0 (0.95.ltoreq.c.ltoreq.1.0), still more preferably 0.99 or more and not more than 1.0 (0.99.ltoreq.c.ltoreq.1.0).

However, the forgetting coefficient c must be selected so that the estimated value (solution) of the state variable obtained by solving the equation (68) does not diverge. If the estimated value (solution) of the state variable obtained by solving the expression (68) does not diverge, the estimated value (solution) of the state variable becomes the most accurate solution when the value of the forgetting coefficient c is 1.0. However, when the value of the forgetting coefficient c is 1.0, the estimated value (solution) of the state variable obtained by solving the expression (68) is highly likely to diverge (solution cannot be obtained).

From such a viewpoint, the forgetting coefficient c may be selected so that the upper limit value of the forgetting coefficient c is smaller than 1.0. That is, the value of the forgetting coefficient c can be selected from, for example, values exceeding 0.0 and less than 1.0 (0.0 < c < 1.0), preferably 0.90 or more and less than 1.0 (0.90. Ltoreq.c < 1.0), more preferably 0.95 or more and less than 1.0 (0.95. Ltoreq.c < 1.0), and still more preferably 0.99 or more and less than 1.0 (0.99. Ltoreq.c < 1.0).

When the value of the forgetting coefficient c is 1.0, the equation (68) is the equations of (9), (10), (13) to (21), and (34) to (39) (the equation itself is expressed by using only the state variables).

The state variable deriving unit 504 uses the longitudinal force T generated by the 1 st frequency adjusting unit 503 ₁ ～T ₄ Time-series data of high-frequency components of (2) to derive a conversion variable e ₁ ～e ₄ The actual value of (2) is substituted into the equations (34) to (37), and the longitudinal force T generated by the 1 st frequency adjusting unit 503 is applied ₁ ～T ₄ Time-series data of high-frequency components of (2) as front-rear direction force T ₁ ～T ₄ The measured value of (2) is substituted into the equations (38) to (39) to solve the equation (68), thereby determining the estimated value of the state variable shown in the equation (44). The method of solving the equation of the expression (68) can be realized by a known numerical method (euler method or the like), for example. Therefore, the state variable deriving unit 504 does not use time-series data of the measured value of the acceleration in the left-right direction of the vehicle body 11, time-series data of the measured value of the acceleration in the left-right direction of the bogies 12a, 12b, and time-series data of the measured value of the acceleration in the left-right direction of the axles 13a to 13d when deriving the estimated value of the state variable. In addition, the observation equation is not used.

As described above, in the present embodiment, the inspection apparatus 500 applies the longitudinal force T to the equation obtained by multiplying the forgetting coefficient c by the term other than the time-differentiated term x·of the state variable in the state equation in which the system noise W is set to 0 (zero) ₁ ～T ₄ Measured value of (2) and conversion variable e ₁ ～e ₄ Deriving state variables from actual values of (2) Therefore, the end irregularity y can be derived without greatly reducing the accuracy without using the measured values of the acceleration in the lateral direction of the vehicle body 11, the bogies 12a, 12b, and the wheel axles 13a to 13d _R1 ～y _R4 (final open-end irregularity y _R )。

In this embodiment, various modifications described in embodiment 1 can be employed. When the equation of motion contains an external force or the like independent of the equation of state X, the expression (68) is expressed as the following expression (69).

X·＝c(ΦX+Gf) …(69)

G is a vector that holds a term in the equation of motion that is independent of the equation of state. F is a matrix corresponding to the vector G.

(embodiment 3)

Next, embodiment 3 will be described.

In embodiment 1 and embodiment 2, the final passing-end irregularity y is checked by the inspection device 500 mounted on the railway vehicle _R The case of performing the calculation is described as an example. In contrast, in the present embodiment, the data processing device to which a part of the functions of the inspection device 500 are attached is disposed in the command center. The data processing device receives measurement data transmitted from a railway vehicle, and calculates a final end irregularity y using the received measurement data _R . As described above, in the present embodiment, the functions of the inspection device 500 according to embodiment 1 and embodiment 2 are shared by the railway vehicle and the command center. The main difference between the present embodiment and embodiments 1 and 2 is the configuration and processing based on this case. Therefore, in the description of the present embodiment, the same reference numerals and the like as those given in fig. 1 to 10 are given to the same parts as those of embodiment 1 and embodiment 2, and detailed description thereof is omitted. The present embodiment can be applied to any of embodiments 1 and 2.

Fig. 11 is a diagram showing an example of the structure of the inspection system. In fig. 11, the inspection system has data collection devices 1110a, 1110b and a data processing device 1120. Fig. 11 also shows an example of the functional configuration of the data collection devices 1110a and 1110b and the data processing device 1120. The hardware of the data collection devices 1110a and 1110b and the data processing device 1120 can be realized by, for example, the hardware shown in fig. 6. Therefore, detailed descriptions of hardware configurations of the data collection devices 1110a and 1110b and the data processing device 1120 are omitted.

Each of the railway vehicles is mounted with 1 data collection devices 1110a and 1110b. The data processing device 1120 is configured at a command center. The command center centrally manages the operation of a plurality of railway vehicles, for example.

[ data collecting devices 1110a, 1110b ]

The data collection devices 1110a, 1110b can be implemented by the same device. The data collection devices 1110a and 1110b include data acquisition units 1111a and 1111b and data transmission units 1112a and 1112b.

< data acquisition units 1111a and 1111b >

The data acquisition units 1111a and 1111b have the same functions as the data acquisition unit 502. That is, the data acquisition units 1111a and 1111b acquire time-series data of the measurement values of the longitudinal force in the same manner as the data acquisition unit 502. The configuration for obtaining the measurement value of the longitudinal force is the same as that described in embodiment 1.

[ data transmitting units 1112a, 1112b ]

The data transmission units 1112a and 1112b transmit time-series data of the measured values of the longitudinal force acquired by the data acquisition units 1111a and 1111b to the data processing apparatus 1120. In the present embodiment, the data transmission units 1112a and 1112b transmit time-series data of the measured values of the longitudinal force acquired by the data acquisition units 1111a and 1111b to the data processing apparatus 1120 by wireless communication. At this time, the data transmitting units 1112a and 1112b add the identification numbers of the railway vehicles on which the data collecting devices 1110a and 1110b are mounted to the time-series data of the measured values of the front-rear force acquired by the data acquiring units 1111a and 1111 b. In this way, the data transmission units 1112a and 1112b transmit time-series data of the measured values of the longitudinal force to which the identification numbers of the railway vehicles are added.

< data processing apparatus 1120>

[ data receiving section 1121]

The data receiving unit 1121 receives time-series data of the measured values of the front-rear force transmitted by the data transmitting units 1112a and 1112 b. The time-series data of the measured value of the longitudinal force is added with the identification number of the railway vehicle, which is the source of the time-series data of the measured value of the longitudinal force.

[ data storage 1122]

The data storage unit 1122 stores time-series data of the measured values of the front-rear force received by the data receiving unit 1121. The data storage unit 1122 stores time-series data of measured values of the longitudinal force for each identification number of the railway vehicle. The data storage unit 1122 determines the position of the railway vehicle at the time of receiving the time-series data of the measured value of the longitudinal force based on the current operating condition of the railway vehicle and the time of receiving the time-series data of the measured value of the longitudinal force, and stores the information of the determined position and the time-series data of the measured value of the longitudinal force in association with each other. The data collection devices 1110a and 1110b may collect information on the current position of the railway vehicle, and include the collected information in time-series data of the measured values of the force in the front-rear direction.

[ data read section 1123]

The data reading unit 1123 reads time-series data of the measured values of the front-rear force stored in the data storage unit 1122. The data reading unit 1123 can read out data designated by the operator from among the time-series data of the measured values of the front-rear force stored in the data storage unit 1122. The data reading unit 1123 may read time-series data of the measured value of the longitudinal force that satisfies the predetermined condition at a predetermined timing. In the present embodiment, for example, time-series data of the measured value of the longitudinal force read by the data reading unit 1123 is determined based on at least one of the identification number and the position of the railway vehicle.

The storage unit 501, the 1 st frequency adjustment unit 503, the state variable derivation unit 504, the 2 nd frequency adjustment unit 505, the track state derivation unit 506, and the output unit 507 are the same as those described in embodiment 1. Thus, a detailed description thereof is omitted herein. The 1 st frequency adjustment unit 503 determines the longitudinal force T by using the time-series data of the longitudinal force measurement values read by the data reading unit 1123 instead of the time-series data of the longitudinal force measurement values acquired by the data acquisition unit 502 ₁ ～T ₄ Time-series data of high-frequency components of (a) are provided.

< summary >

As described above, in the present embodiment, the data collection devices 1110a and 1110b mounted on the railway vehicle collect time-series data of the measured values of the longitudinal force and transmit the time-series data to the data processing device 1120. The data processing device 1120 disposed in the command center stores time-series data of the measured values of the front-rear force received from the data collection devices 1110a, 1110b, and calculates the final open-end irregularity y using the stored time-series data of the measured values of the front-rear force _R . Thus, in addition to the effects described in embodiment 1 and embodiment 2, the following effects are exhibited, for example. That is, the data processing device 1120 reads out the measurement data at an arbitrary timing, thereby calculating the final end irregularity y at an arbitrary timing _R . In addition, the data processing device 1120 is capable of outputting the final throughput irregularity y at the same location _R Is a time series change of (a). In addition, the data processing device 1120 can output the final end-of-line irregularity y of a plurality of routes for each route _R 。

< modification >

In this embodiment, a case where measurement data is directly transmitted from the data collection devices 1110a and 1110b to the data processing device 1120 will be described as an example. However, this need not be done. For example, cloud computing may also be utilized to build inspection systems.

In addition, in this embodiment, various modifications described in embodiment 1 and embodiment 2 can be employed.

In embodiments 1 and 2, a case where the storage unit 501, the data acquisition unit 502, the 1 st frequency adjustment unit 503, the state variable derivation unit 504, the 2 nd frequency adjustment unit 505, the track state derivation unit 506, and the output unit 507 are included in one device will be described as an example. However, this need not be the case. The functions of the storage unit 501, the data acquisition unit 502, the 1 st frequency adjustment unit 503, the state variable derivation unit 504, the 2 nd frequency adjustment unit 505, the track state derivation unit 506, and the output unit 507 may be realized by a plurality of devices. In this case, the inspection system is constituted using the plurality of devices.

(calculation example)

Next, a calculation example will be described. In this calculation example, the final open-end irregularity y is derived by the method of embodiment 1 _R And deriving the final open-end irregularity y by the method of embodiment 2 _R . In the method according to embodiment 1, at the time of data assimilation, a value (constant value) given as a measurement value of an observation variable is set to 0 (zero). In the method of embodiment 2, the forgetting coefficient c is set to 0.9987.

In the method of embodiment 1, the final through-end irregularity y is derived by directly applying a measurement value (i.e., the method described in patent literature 1) instead of applying a predetermined constant value to a value (measurement value of acceleration in the lateral direction of the vehicle body 11, the bogies 12a, 12b, and the axles 13a to 13 d) which is applied as a measurement value of an observation variable _R 。

Fig. 12 is a graph showing the present calculation example, and showing the curvature 1/R of the track 16 to be derived from the end irregularity and the running speed v of the railway vehicle. In fig. 12, a curve 1201 represents the running speed of the railway vehicle, and a curve 1202 represents the curvature 1/R of the track 16. In fig. 12, the horizontal axis represents the elapsed time (seconds) from the reference time when the reference time is set to 0 (zero).

Fig. 13A and 13B showIn this example, a graph showing the distribution of eigenvalues of the autocorrelation matrix R is shown. Fig. 13A shows a front-rear direction force T against the wheel shaft 13A ₁ The distribution of the eigenvalues of the autocorrelation matrix R of fig. 13B shows the front-rear direction force T against the wheel shaft 13B ₂ Is provided for the distribution of eigenvalues of the autocorrelation matrix R.

FIG. 14 shows the present example of calculation and shows the force T in the front-rear direction ₁ 、T ₂ Time-series data of measurement value y of (2), and front-rear direction force T ₁ 、T ₂ Is y-a predictive value of (2) _k A graph of (i) time series data of low frequency components included in time series data of measured value y of force in the front-rear direction. In FIG. 14, the measured value represents time-series data of the measured value y of the front-rear force, and the bias represents the predicted value y≡c of the front-rear force _k Is provided). In fig. 14, the horizontal axis represents the elapsed time (seconds) from the reference time point when the reference time point is set to 0 (zero), and represents the longitudinal force T ₁ ～T ₄ Measurement time and calculation time of (a).

FIG. 15 shows the present example of calculation and shows the force T in the front-rear direction ₁ 、T ₂ A graph of time-series data of high frequency components of (a) is provided. Force T in the front-rear direction ₁ 、T ₂ Is obtained by applying a force T from the front-rear direction shown in FIG. 14 ₁ 、T ₂ Subtracting the longitudinal force T from the time-series data of the measured value y of (2) ₁ 、T ₂ Is y-a predictive value of (2) _k Obtained from the time series data of the above-mentioned data storage medium. In fig. 15, the horizontal axis represents the elapsed time (seconds) from the reference time point when the reference time point is set to 0 (zero), and represents the longitudinal force T ₁ 、T ₂ The computation time of the time series data of the high frequency component of (a).

Fig. 16A and 16B show the use of the front-rear direction force T shown in fig. 15 ₁ 、T ₂ The amount y of the open-end irregularity derived by the method of embodiment 1 and the method described in patent document 1 _R Is a diagram of (a). In fig. 16A, the calculated value indicates the terminal end derived by the method described in patent document 1Irregular amount y _R The measured value represents the through-end irregularity y _R Is measured by the above method. In fig. 16B, the calculated value represents the open-end irregularity amount y derived by the method of embodiment 1 _R The measured value represents the through-end irregularity y _R Is measured by the above method. Here, as the open-end irregularity y _R Using the through-end irregularities y at the location of the axle 13a _R1 Through-end irregularity y at the location of the axle 13b _R2 Average value of (2). The measurement value shown in fig. 16A is the same as the measurement value shown in fig. 16B. In fig. 16A and 16B, the horizontal axis represents the elapsed time (seconds) from the reference time point when the reference time point is 0 (zero), and is equal to the open-end irregularity y _R The time at which the position exists corresponds. In fig. 16A, the data of a portion having a small distance from the departure point of the railway vehicle is not shown for convenience of illustration.

Fig. 17A shows the use of the front-rear direction force T shown in fig. 15 ₁ 、T ₂ The through-terminal irregularity amount y derived by the method of embodiment 2 _R Is a diagram of (a). Fig. 17B shows the front-rear direction force T shown in fig. 15 ₁ 、T ₂ The amount y of the open-end irregularity derived by using the method described in patent document 1 _R Is a diagram of (a). In fig. 17A, the calculated value represents the open-end irregularity amount y derived by the method described in patent document 1 _R The measured value represents the passing through end irregularity y _R Is measured by the above method. In fig. 17B, the calculated value represents the open-end irregularity amount y derived by the method of embodiment 2 _R The measured value represents the through-end irregularity y _R Is measured by the above method. Here, as the open-end irregularity y _R Using the through-end irregularities y at the location of the axle 13a _R1 Through-end irregularity y at the location of the axle 13b _R2 Average value of (2). The measurement values shown in fig. 17A are the same as those shown in fig. 17B (these measurement values are also the same as those shown in fig. 16A and 16B). The horizontal axis in fig. 17A and 17B is the case where the reference time is set to 0 (zero)The time (seconds) elapsed from the reference time is equal to the open-end irregularity y _R The time at which the position exists corresponds. In fig. 17A and 17B, the data of the portion having a small distance from the departure point of the railway vehicle is not shown for convenience of illustration.

When the calculated value of fig. 16A is compared with the calculated value of fig. 16B, it is known that the end irregularity y is derived by the method of embodiment 1 _R And the end irregularity y derived by the method described in patent document 1 _R Consistent with good accuracy. In addition, it is found that the calculated value and the measured value agree with each other with good accuracy. Similarly, when the calculated value of fig. 17A is compared with the calculated value of fig. 17B, it is known that the end irregularity y is derived by the method of embodiment 2 _R And the end irregularity y derived by the method described in patent document 1 _R Consistent with good accuracy. In addition, it is found that the calculated value and the measured value agree with each other with good accuracy. When the calculated value of fig. 16B is compared with the calculated value of fig. 17B, it is found that the same amount y of the common-end irregularity can be derived in both the method of embodiment 1 and the method of embodiment 2, which are almost the same _R 。

(other embodiments)

The embodiments of the present invention described above can be realized by executing a program by a computer. The computer-readable recording medium storing the program described above and the computer program product such as the program described above can also be applied as an embodiment of the present invention. As the recording medium, for example, a floppy disk, a hard disk, an optical disk, a magneto-optical disk, a CD-ROM, a magnetic tape, a nonvolatile memory card, a ROM, or the like can be used.

The embodiments of the present invention described above are merely specific examples for carrying out the present invention, and the technical scope of the present invention is not limited to these examples. That is, the present invention can be implemented in various forms without departing from the technical spirit or main features thereof.

The description of patent document 1 and the accompanying drawings can be entirely incorporated herein.

Industrial applicability

The present invention can be used for, for example, inspecting railway vehicles.

Claims (16)

1. An inspection system, comprising:

a data acquisition unit that acquires data of a measurement value of a force in the front-rear direction as data of a measurement value measured by running a railway vehicle having a vehicle body, a bogie, and an axle on a track;

a state variable deriving unit that derives a state variable to be determined in a state equation configured by using a motion equation describing the motion of the railway vehicle, using the measured value of the front-rear force; and

a track state deriving unit for deriving information reflecting the state of the track,

the front-rear force is a force in the front-rear direction generated in a member disposed between the wheel axle and the bogie provided with the wheel axle, and is a force determined based on a difference between an angular displacement in a yaw direction of the wheel axle and an angular displacement in a yaw direction of the bogie provided with the wheel axle,

The above-mentioned parts are parts for supporting the axleboxes,

the front-rear direction is a direction along a traveling direction of the railway vehicle,

the yaw direction is a rotation direction using an up-down direction which is a direction perpendicular to the rail as a rotation axis,

the state equation is an equation described using the state variable, the front-rear direction force, and the conversion variable,

the state variables include a displacement and a velocity of the bogie in a left-right direction, an angular displacement and an angular velocity of the bogie in a yaw direction, an angular displacement and an angular velocity of the bogie in a roll direction, a displacement and a velocity of the wheel axle in a left-right direction, and an angular displacement of an air spring attached to the railway vehicle in a roll direction, and do not include an angular displacement and an angular velocity of the wheel axle in a yaw direction,

the roll direction is a rotation direction using the front-rear direction as a rotation axis,

the conversion variable is a variable that converts an angular displacement in a yaw direction of the wheel axle and an angular displacement in a yaw direction of the bogie to each other,

the track state deriving means derives an estimated value of the angular displacement of the wheel shaft in the yaw direction using the angular displacement of the bogie in the yaw direction, which is one of the state variables derived by the state variable deriving means, and the actual value of the conversion variable, and derives information reflecting the state of the track using the derived estimated value of the angular displacement of the wheel shaft in the yaw direction,

The actual value of the conversion variable is derived using the measured value of the front-rear force,

the state variable deriving means derives the state variable without using measured values of acceleration in the lateral direction of the bogie, the wheel axle, and the vehicle body during a period in which the measured values of the front-rear force are obtained.

2. The inspection system of claim 1, wherein the inspection system,

the state variable deriving means derives the state variable by performing an operation using a filter for data assimilation using the state equation and the observation equation,

the above observation equation is an equation described using the observation variable and the above conversion variable,

the observation variable includes acceleration in the left-right direction of the bogie and the wheel axle,

the state variable deriving means derives, at the time of data assimilation, the state variable in which an error of the calculated value of the observed variable with respect to the constant value or an expected value of the error is minimized, by using the state equation in which the measured value of the front-rear force and the actual value of the converted variable are substituted and the observation equation in which the actual value of the converted variable is substituted, with the value given as the measured value of the observed variable being a predetermined constant value.

3. The inspection system of claim 2, wherein the inspection system,

the constant value is 0.

4. An inspection system according to claim 2 or 3, wherein,

the equation of state is constructed using an equation of motion describing a left-right direction motion of the wheel axle, an equation of motion describing a left-right direction motion of the bogie, an equation of motion describing a yaw direction motion of the bogie, an equation of motion describing a roll direction motion of the bogie, and an equation of motion describing a roll direction motion of the air spring,

the equation of motion describing the yaw-direction motion of the bogie is described using the fore-and-aft force instead of the angular displacement and angular velocity of the wheel axle in the yaw direction,

the observation equation is constructed using a motion equation describing a motion of the wheel axle in a left-right direction and a motion equation describing a motion of the bogie in the left-right direction,

the equation of motion describing the motion of the wheel axle in the left-right direction is an equation of motion described using the conversion variable instead of the angular displacement of the wheel axle in the yaw direction,

The conversion variable is represented by a difference between an angular displacement in a yaw direction of the bogie and an angular displacement in a yaw direction of the wheel axle.

5. The inspection system of claim 4, wherein the inspection system,

the above-described equation of state is also constructed using an equation of motion describing a motion in the left-right direction of the above-described vehicle body, an equation of motion describing a motion in the yaw direction of the above-described vehicle body, an equation of motion describing a motion in the roll direction of the above-described vehicle body, and an equation of motion describing a motion in the yaw direction of a yaw damper mounted to the above-described railway vehicle,

the observation equation is also constructed using a motion equation describing the motion of the vehicle body in the left-right direction,

the observation variable further includes acceleration in the left-right direction of the vehicle body,

the state variables include a displacement and a velocity in the left-right direction of the vehicle body, an angular displacement and an angular velocity in the yaw direction of the vehicle body, an angular displacement and an angular velocity in the roll direction of the vehicle body, and an angular displacement in the yaw direction of the yaw damper.

6. The inspection system of claim 2, wherein the inspection system,

the filter is a kalman filter.

7. The inspection system of claim 1, wherein the inspection system,

the state variable deriving means derives the state variable by solving, without solving the state equation, a formula representing a motion equation describing the motion of the railway vehicle using the state variable, the longitudinal force, and the conversion variable, and a formula substituted with a measured value of the longitudinal force and an actual value of the conversion variable.

8. The inspection system of claim 7, wherein the inspection system,

the state variable deriving means derives the state variable by using, instead of the state equation, a formula in which a formula describing a motion equation of the railway vehicle motion is expressed using the state variable, the longitudinal force, and the conversion variable, the formula being changed so that a time change of the state variable becomes smaller than the formula, and by substituting a measured value of the longitudinal force and an actual value of the conversion variable.

9. The inspection system of claim 8, wherein the inspection system,

the state variable deriving means derives the state variable by solving a formula obtained by multiplying each term of the 1 st order time differential of the state variable by a forgetting coefficient by a term connected by an equal sign, among formulas expressing an equation of motion describing the motion of the railway vehicle using the state variable, the fore-and-aft direction force, and the conversion variable,

The forgetting coefficient is a predetermined value of 0.95 or more and less than 1.

10. The inspection system of any one of claims 7 to 9, wherein,

the equations of motion describing the motion of the railway vehicle include equations of motion describing the left-right direction of the wheel axle, equations of motion describing the left-right direction of the bogie, equations of motion describing the yaw direction of the bogie, equations of motion describing the roll direction of the bogie, and equations of motion describing the roll direction of the air spring,

the equation of motion describing the motion of the wheel axle in the left-right direction is an equation of motion described using the conversion variable instead of the angular displacement of the wheel axle in the yaw direction,

the equation of motion describing the yaw-direction motion of the bogie is described using the fore-and-aft force instead of the angular displacement and angular velocity of the wheel axle in the yaw direction,

the conversion variable is represented by a difference between an angular displacement in a yaw direction of the bogie and an angular displacement in a yaw direction of the wheel axle.

11. The inspection system of claim 10, wherein the inspection system,

the equations of motion describing the motions of the above-described railway vehicles also include equations of motion describing the motions of the above-described vehicle body in the left-right direction, equations of motion describing the motions of the above-described vehicle body in the yaw direction, equations of motion describing the motions of the above-described vehicle body in the roll direction, and equations of motion describing the motions of the yaw dampers mounted to the above-described railway vehicles,

the state variables further include a displacement and a velocity in the left-right direction of the vehicle body, an angular displacement and an angular velocity in the yaw direction of the vehicle body, an angular displacement and an angular velocity in the roll direction of the vehicle body, and an angular displacement in the yaw direction of the yaw damper.

12. An inspection system according to any one of claims 1 to 3, 7 to 9,

the track state deriving means derives a free end irregularity of the track as information reflecting a state of the track based on a displacement and a velocity in a left-right direction of the bogie, which are one of the state variables derived by the state variable deriving means, a displacement and a velocity in a left-right direction of the wheel axle, which are one of the state variables derived by the state variable deriving means, the estimated value of the angular displacement of the wheel axle in the yaw direction, the measured value of the fore-and-aft direction force, and a motion equation describing a motion in the yaw direction of the wheel axle,

The equation of motion describing the yaw-direction motion of the wheel axle includes, as variables, the fore-and-aft force and the amount of end irregularity of the rail.

13. An inspection system according to any one of claims 1 to 3, 7 to 9,

the track state deriving means derives, as information reflecting the state of the track, a lateral pressure, which is a stress in the lateral direction between the wheels of the wheel axle and the track, based on the angular displacement in the yaw direction of the wheel axle and the speed in the lateral direction of the wheel axle, which is one of the state variables.

14. An inspection system according to any one of claims 1 to 3, 7 to 9,

further comprising a frequency adjustment means for reducing the signal intensity of a low-frequency component generated by the running of the railway vehicle on the curved portion of the track from time-series data of a physical quantity whose value varies according to the state of the railway vehicle,

the frequency adjustment means includes 1 st frequency adjustment means for reducing the signal intensity of a low frequency component generated by the running of the railway vehicle on the curved portion of the track from time-series data of the measured value of the longitudinal force, which is one of the physical quantities,

The state variable deriving means derives the state variable using the value of the front-rear force whose signal strength of the low frequency component is reduced by the 1 st frequency adjusting means.

15. An inspection method comprising:

a data acquisition step of acquiring data of a measurement value of a force in the front-rear direction as data of a measurement value measured by running a railway vehicle having a vehicle body, a bogie, and an axle on a track;

a state variable deriving step of deriving a state variable to be determined in a state equation configured by using a motion equation describing the motion of the railway vehicle, using the measured value of the front-rear force; and

a track state deriving step of deriving information reflecting the state of the track,

the front-rear force is a force in the front-rear direction generated in a member disposed between the wheel axle and the bogie provided with the wheel axle, and is a force determined based on a difference between an angular displacement in a yaw direction of the wheel axle and an angular displacement in a yaw direction of the bogie provided with the wheel axle,

the above-mentioned parts are parts for supporting the axleboxes,

The front-rear direction is a direction along a traveling direction of the railway vehicle,

the yaw direction is a rotation direction using an up-down direction which is a direction perpendicular to the rail as a rotation axis,

the state equation is an equation described using the state variable, the front-rear direction force, and the conversion variable,

the state variables include a displacement and a velocity of the bogie in a left-right direction, an angular displacement and an angular velocity of the bogie in a yaw direction, an angular displacement and an angular velocity of the bogie in a roll direction, a displacement and a velocity of the wheel axle in a left-right direction, and an angular displacement of an air spring attached to the railway vehicle in a roll direction, and do not include an angular displacement and an angular velocity of the wheel axle in a yaw direction,

the roll direction is a rotation direction using the front-rear direction as a rotation axis,

the conversion variable is a variable that converts an angular displacement in a yaw direction of the wheel axle and an angular displacement in a yaw direction of the bogie to each other,

the track state deriving step derives an estimated value of the angular displacement of the wheel shaft in the yaw direction using the angular displacement of the bogie in the yaw direction, which is one of the state variables derived in the state variable deriving step, and the actual value of the conversion variable, and derives information reflecting the state of the track using the derived estimated value of the angular displacement of the wheel shaft in the yaw direction,

The actual value of the conversion variable is derived using the measured value of the front-rear force,

the state variable deriving step derives the state variable without using measured values of acceleration in the lateral direction of the bogie, the wheel axle, and the vehicle body during a period in which the measured values of the front-rear force are obtained.

16. A computer-readable storage medium storing a program, characterized in that,

the above program causes a computer to execute:

a data acquisition step of acquiring data of a measurement value of a force in the front-rear direction as data of a measurement value measured by running a railway vehicle having a vehicle body, a bogie, and an axle on a track;

a state variable deriving step of deriving a state variable to be determined in a state equation configured by using a motion equation describing the motion of the railway vehicle, using the measured value of the front-rear force; and

a track state deriving step of deriving information reflecting the state of the track,

the front-rear force is a force in the front-rear direction generated in a member disposed between the wheel axle and the bogie provided with the wheel axle, and is a force determined based on a difference between an angular displacement in a yaw direction of the wheel axle and an angular displacement in a yaw direction of the bogie provided with the wheel axle,

The above-mentioned parts are parts for supporting the axleboxes,

the front-rear direction is a direction along a traveling direction of the railway vehicle,

the yaw direction is a rotation direction using an up-down direction which is a direction perpendicular to the rail as a rotation axis,

the state equation is an equation described using the state variable, the front-rear direction force, and the conversion variable,

the state variables include a displacement and a velocity of the bogie in a left-right direction, an angular displacement and an angular velocity of the bogie in a yaw direction, an angular displacement and an angular velocity of the bogie in a roll direction, a displacement and a velocity of the wheel axle in a left-right direction, and an angular displacement of an air spring attached to the railway vehicle in a roll direction, and do not include an angular displacement and an angular velocity of the wheel axle in a yaw direction,

the roll direction is a rotation direction using the front-rear direction as a rotation axis,

the conversion variable is a variable that converts an angular displacement in a yaw direction of the wheel axle and an angular displacement in a yaw direction of the bogie to each other,

the track state deriving step derives an estimated value of the angular displacement of the wheel shaft in the yaw direction using the angular displacement of the bogie in the yaw direction, which is one of the state variables derived in the state variable deriving step, and the actual value of the conversion variable, and derives information reflecting the state of the track using the derived estimated value of the angular displacement of the wheel shaft in the yaw direction,

The actual value of the conversion variable is derived using the measured value of the front-rear force,

the state variable deriving step derives the state variable without using measured values of acceleration in the lateral direction of the bogie, the wheel axle, and the vehicle body during a period in which the measured values of the front-rear force are obtained.