CN107380204B - Track geometric parameter detection vehicle and track geometric parameter detection method - Google Patents
Track geometric parameter detection vehicle and track geometric parameter detection method Download PDFInfo
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- CN107380204B CN107380204B CN201710685110.XA CN201710685110A CN107380204B CN 107380204 B CN107380204 B CN 107380204B CN 201710685110 A CN201710685110 A CN 201710685110A CN 107380204 B CN107380204 B CN 107380204B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61K—AUXILIARY EQUIPMENT SPECIALLY ADAPTED FOR RAILWAYS, NOT OTHERWISE PROVIDED FOR
- B61K9/00—Railway vehicle profile gauges; Detecting or indicating overheating of components; Apparatus on locomotives or cars to indicate bad track sections; General design of track recording vehicles
- B61K9/08—Measuring installations for surveying permanent way
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Abstract
The invention provides a track geometric parameter detection vehicle and a track geometric parameter detection method aiming at groove type track data detection. The track geometric parameter detection vehicle and the track geometric parameter detection method provided by the invention realize the data detection of the groove-shaped track, and meanwhile, the generated geometric parameter data has higher accuracy through error correction.
Description
Technical Field
The invention relates to a track parameter detection device and a track parameter detection method, in particular to a track geometric parameter detection vehicle based on a tramcar groove-shaped track and a track geometric parameter detection method.
Background
Along with the rapid promotion of urban rail transit construction in China, modern trams are rapidly developed. The track is used as a basic carrier of the tram, and performance parameter detection on the track is an important basic work for guaranteeing safe operation of the tram. Modern tram tracks run throughout cities, while high-speed rail tracks are mostly erected from city to city, the track type of trams is not the same as that of high-speed rail. The modern tramcar adopts embedded design, the main line of the steel rail is a groove type steel rail, and a contact net power supply system, a super capacitor power supply system or a ground power supply system and the like are adopted on a power supply system, wherein the ground power supply system technology is in a state of leading technology at home and abroad, the power supply system utilizes a power supply rail in the middle of a track to carry out contact power supply, and the track design is more complex than that of a high-speed railway track, so that new technical difficulties are brought to the parameter detection of the track.
The existing track detection vehicle for detecting railway I-shaped tracks comprises a vehicle body, and a GPS positioning device, a photoelectric encoder, a vertical acceleration sensor, a transverse acceleration sensor and a camera which are arranged on the vehicle body. The main stress surface of the I-shaped rail is the upper surface of the rail, the main wear surface is the upper surface of the rail and the inner side surface positioned on one side of the upper surface of the rail, the camera can detect the track gauge and track direction data of the rail, and the acceleration sensor can detect the data such as height, abrasion and the like.
The problem that exists of current this kind of track detection car is, owing to bury the groove type rail and the I-shaped rail structure difference and the operating mode is different in ground, still be provided with the power supply rail between some groove type rails, the parameter of power supply rail also needs to be detected, adopt camera and acceleration sensor to be unable to detect the geometric parameter data of groove type rail and power supply rail, one of them main wearing and tearing point of groove type rail is located the side in groove, the wearing and tearing state of groove type rail can't be detected to the camera, and the error that current track detection car can't lead to the fact the automobile body gradient is rectified, lead to the track data that the final detection obtained to have the deviation.
Disclosure of Invention
The first object of the present invention is to provide a track geometry detecting vehicle for use with a grooved rail and having an error correcting function.
The second object of the present invention is to provide a method for detecting geometric parameters of a track, which is used for a groove-shaped track and has an error correction function.
The track geometric parameter detection vehicle comprises a vehicle body, a track wheel set and a sensor group, wherein the track wheel set and the sensor group are arranged on the vehicle body, the sensor group comprises a photoelectric encoder, an acceleration sensor, a laser displacement sensor group and a gyroscope sensor, the track wheel set comprises a left track wheel and a right track wheel, and the photoelectric encoder is arranged at a rotating shaft connected with the track wheel set; the laser displacement sensor group comprises at least three laser displacement sensors; an acceleration sensor and a laser displacement sensor are arranged at the transverse position of the left rail wheel and the transverse position of the right rail wheel, and a laser displacement sensor is arranged at the central position between the left rail wheel and the right rail wheel.
According to the scheme, the laser displacement sensor group and the gyroscope sensor are arranged on the vehicle body, the laser displacement sensor can acquire profile point coordinate data of the cross section of the groove-shaped rail buried in the ground, the two laser displacement sensors on the two sides obtain a straight line fitted by the profile points of the top surface, the straight line has a slope in the coordinates obtained by combining the two laser displacement sensors, so that the inclination angle of the vehicle body relative to the rail is known, the profile point coordinate data of the groove-shaped rail is converted again through the processor, the rail data correction is realized, the rail profile data is more accurate, the corrected rail data is compared with the standard rail data, and the practical parameters such as the track gauge, the abrasion degree, the horizontal value, the unevenness of the power supply rail and the like of the groove-shaped rail can be accurately acquired.
The track geometric parameter detection vehicle further comprises a rotating device, wherein the rotating device comprises a fixed part and a rotating part which are connected with each other, the rotating part can rotate along a first axis and a second axis relative to the fixed part, and the first axis and the second axis are mutually perpendicular; the fixed part is connected with the vehicle body, and the rotating part is connected with the laser displacement sensor.
From the above, the rotation device realizes the adjustment of the emergent angle of the laser displacement sensor, so that the laser displacement sensor can more accurately acquire the contour coordinate data of the track.
The track geometric parameter detection vehicle further comprises a road wheel and a hydraulic device, wherein the road wheel is arranged at the lower part of the vehicle body, the hydraulic device is connected between the track wheel and the vehicle body, and the hydraulic device drives the track wheel to move so that the horizontal position of the lowest point of the track wheel is positioned below the horizontal position of the lowest point of the road wheel.
From the above, the track geometric parameter detection vehicle can utilize the switching use between road wheels and track wheels to realize the conversion between land running and track running.
The track geometric parameter detection vehicle further comprises a cantilever and a detection beam, wherein the detection beam is connected to the vehicle body through the cantilever, and the detection beam is transversely arranged; the sensor group is all set up on detecting the roof beam.
From the above, the sensor group is uniformly arranged on the detection beam, so that the sensor group is more convenient for a detector to uniformly assemble, disassemble, maintain, debug and use.
The second object of the present invention is to provide a method for detecting geometric parameters of a track, the method for detecting geometric parameters of a track using the vehicle for detecting geometric parameters of a track provided by the present invention, the method for detecting geometric parameters of a track comprising: the laser displacement sensor group acquires track point data and sends the track point data to the processor; the processor corrects errors generated by the inclination angle of the vehicle body according to the track point data to generate corrected data; the processor generates actual geometry data from the corrected data.
According to the scheme, the laser displacement sensors acquire track point data of the cross section profile of the groove-shaped track, top surface profile points obtained by the two laser displacement sensors on two sides are fitted to form a straight line, the straight line has a slope in coordinates obtained by combining the two laser displacement sensors, so that the inclination angle of a vehicle body relative to the track is known, the track point data of the three laser displacement sensors are converted through the processor to generate corrected data of the profile points of the groove-shaped track and the power supply track, and the corrected data are compared with standard track data to accurately acquire actual data such as abrasion degree, horizontal value and unevenness of the groove-shaped track. The data errors are effectively corrected, and accurate data of the groove type rail and the power supply rail are finally obtained.
The method further comprises the steps that the laser displacement sensor group acquires track point data and sends the track point data to the processor, the photoelectric encoder sends out pulse signals, and the laser displacement sensor group acquires the track point data according to the pulse signals.
From the above, the laser displacement sensor emits signals according to the pulse signals, so that equidistant multiple groups of track data are obtained, variance calculation is performed according to the multiple groups of track data, and more accurate track data can be obtained.
After the photoelectric encoder sends out the pulse signal, the acceleration sensor acquires acceleration data according to the pulse signal, and the processor generates the irregularity data according to the acceleration data.
From the above, the data of the irregularity of the track can be obtained by performing the second integration using the acceleration data.
The processor corrects errors generated by the inclination angle of the vehicle body according to the track point data to generate corrected data, the gyroscope sensor acquires the data of the inclination angle of the vehicle body relative to the ground according to the pulse signal, and the processor generates horizontal value data according to the corrected data and the data of the inclination angle of the vehicle body.
From the above, the inclination angle of the track to the ground can be obtained based on the obtained inclination data of the vehicle body to the track and the inclination data of the vehicle body to the ground, and then the track gauge data is used to accurately calculate the level value according to the trigonometric function.
In a further aspect, the processor generates actual geometry data from the corrected data, and the processor generates wear value data and centerline deviation data for the power supply rail by comparing the actual profile data with the standard profile data.
From the above, the corrected actual profile data can be compared with the standard profile data to obtain more accurate wear value data.
In a further scheme, the actual geometric parameter data comprises actual contour data, and the processor generates power supply rail unevenness data according to the actual contour data acquired twice in the process of generating the actual geometric parameter data according to the corrected data.
From the above, the power supply rail is formed by connecting multiple sections, the connection sections have unevenness, data acquisition is carried out on the connection sections of two sections of different power supply rails, and the unevenness data between the two connection sections can be obtained by comparing the actual profile data obtained twice.
Drawings
FIG. 1 is a schematic view of a partial structure of an embodiment of a track geometry inspection vehicle according to the present invention.
Fig. 2 is an enlarged view at a in fig. 1.
FIG. 3 is a cross-sectional view of a track in an embodiment of a track geometry detection method of the present invention.
FIG. 4 is a schematic diagram showing the correlation of tilt angles in an embodiment of the track geometry detection method of the present invention.
Fig. 5 is a schematic diagram of track width correlation in an embodiment of the track geometry detection method of the present invention.
FIG. 6 is a schematic diagram of track gauge correlation in an embodiment of the track geometry detection method of the present invention.
FIG. 7 is a diagram showing the relationship between wear values in an embodiment of the track geometry detection method of the present invention.
FIG. 8 is a flowchart of an embodiment of a method for detecting a geometric parameter of a track according to the present invention.
The invention is further described below with reference to the drawings and examples.
Detailed Description
Track geometry inspection vehicle embodiment
Referring to fig. 1, fig. 1 is a schematic partial structure of an embodiment of an inventive track geometry inspection vehicle. The track geometric parameter detection vehicle is a track dual-purpose detection vehicle, and the track geometric parameter detection vehicle comprises a vehicle body 1, a road wheel set 2, a track wheel set 3, a cantilever 41 and a detection beam 42, wherein the road wheel set 2 and the track wheel set 3 are arranged at the lower part of the vehicle body 1, and a rotary shaft 32 connected with the track wheel set 3 is provided with a photoelectric encoder and a corresponding encoding wheel. The track wheel set 3 is fixedly connected to the vehicle body 1 through a hydraulic device 31, the adjustment of the horizontal position of the track wheel set 3 can be realized by driving the hydraulic device 31, and when the horizontal position of the lowest point of the track wheel set 3 is positioned at the horizontal position of the lowest point of the road wheel set 2, the track geometric parameter detection vehicle can realize track running. The cantilever 41 is arranged at the tail part of the vehicle body 1, the detection beam 42 is transversely arranged and hung on the cantilever 41, and a sensor group is arranged on the detection beam 42. The track geometric parameter detection vehicle is used for detecting geometric parameter data of the groove-type track, wherein the geometric parameter data comprise track width, track gauge, abrasion value, horizontal value, irregularity in height, irregularity in track direction, irregularity in power supply track, central line deviation of the power supply track and the like.
Referring to fig. 2, fig. 2 is an enlarged view at a in fig. 1. The sensor groups provided on the detection beam 42 include an acceleration sensor group, a laser displacement sensor group, and a gyro sensor. The track wheel set 3 includes a left track wheel and a right track wheel, a laser displacement sensor 51 and an acceleration sensor 54 are provided at the lateral position where the left track wheel is located, a laser displacement sensor 52 and an acceleration sensor 55 are provided at the lateral position where the right track wheel is located, and a laser displacement sensor 53 and a gyro sensor 56 are provided at the central position between the left track wheel and the right track wheel. Wherein the laser displacement sensors 53 are all connected and mounted to the detection beam 42 by a rotating device 6, the rotating device 6 comprises a fixed part 61, a connecting part 62 and a rotating part 63, the fixed part 61 is fixedly mounted on the lower end surface of the detection beam 42, the connecting part 62 is rotated on the fixed part 61, and the connecting part 62 can rotate along a first axis relative to the fixed part 61; the rotating part 63 is rotatably connected to the connecting part 62, and the rotating part 63 can rotate along a second axis relative to the connecting part 62, wherein the first axis is perpendicular to the second axis; the rotating portion 63 includes a triangular plate member, fixing bolts are provided at three corners of the triangular plate member, and the laser displacement sensor is fixed to the plate member by the fixing bolts, so that the detection direction of the laser displacement sensor can be adjusted by the rotating device in a vertical incidence manner. The fixing portion 61 and the connecting portion 62 of the rotating device 6 are rotatably connected, and the connecting portion 62 and the rotating portion 63 are connected by screw threads to realize locking rotation.
Track geometric parameter detection method embodiment
Referring to fig. 1, 3 and 8, fig. 3 is a sectional view of a groove-type rail track, and fig. 8 is a flowchart of a track geometry parameter detection method. The channel rail track includes a left rail 100, a right rail 200, and a power supply rail 300 positioned between the left rail 100 and the right rail 200, wherein the left rail 100 and the right rail 200 are both channel rails. When the track geometry detecting vehicle runs on the track, the left track wheel is positioned in the left track 100, the right track wheel is positioned in the right track 200, and at this time, the laser displacement sensor 51 and the acceleration sensor 54 arranged at the same lateral position as the left track wheel are positioned directly above the left track 100, and similarly, the laser displacement sensor 52 and the acceleration sensor 55 are positioned directly above the right track 200, and the laser displacement sensor 53 and the gyro sensor 56 are positioned directly above the power supply track 300.
The geometric parameter data of the track to be detected comprises track width, track gauge, abrasion value, horizontal value, irregularity in height, irregularity in track direction, irregularity in power supply track, central line deviation of the power supply track and the like, the basic principle of the operation is that two-dimensional data of the track are obtained through a laser displacement sensor, a processor is used for calculating and comparing according to the two-dimensional data and a gyroscope sensor to obtain the geometric parameter data, and the data of irregularity in height and irregularity in track direction are obtained through an acceleration sensor and are generated through the processor. The processor can be arranged on the track geometric parameter detection vehicle, can also be arranged at a remote control end, and can realize signal interaction with the sensor group through the wireless communication module.
First, step S1 is performed, and the system detects whether the photoelectric encoder has issued a pulse signal. If the pulse signal is sent out, the next step is carried out; if the pulse signal is not sent out, the system continues to detect whether the pulse signal is sent out.
If the pulse signal has been sent, the steps S11, S21 and S31 are continuously executed, where the step S11 is that the pulse signal triggers the laser displacement sensor to send out a detection signal, the step S21 is that the pulse signal triggers the acceleration sensor to send out a detection signal, and the step S31 is that the pulse signal triggers the gyro sensor to send out a detection signal. Step S31, step S21, and step S31 are performed simultaneously.
In step S11, step S21, and step S31, the sensor group emits a detection signal based on the pulse signal emitted from the photoelectric encoder. The photoelectric encoder is installed at the rotating shaft 32, and after each rotation of the track wheel 3 by a set certain angle, the photoelectric encoder sends out a pulse signal, and the laser displacement sensor 51, the laser displacement sensor 52, the laser displacement sensor 53, the acceleration sensor 54, the acceleration sensor 55 and the gyroscope sensor 56 in the sensor group send out detection signals according to the pulse signals, and meanwhile, the processor can generate stroke amount data according to the sending number of the pulse signals.
After the step S11 is performed, the step S12 is performed, and the laser displacement sensor group samples to obtain track point data and corrects the error caused by the inclination angle of the vehicle body, so as to generate corrected data. Referring to fig. 4, fig. 4 is a schematic diagram showing the correlation of tilt angles in an embodiment of the track geometry detection method according to the present invention. The laser displacement sensor 51 and the laser displacement sensor 52 positioned at the corresponding positions of the left rail 100 and the right rail 200 respectively acquire two-dimensional track point data of the left rail 100 and the right rail 200, but since the vehicle body has a left-right inclination angle a and a front-rear inclination angle C relative to the track, the two-dimensional track point data acquired by the laser displacement sensor group has errors due to the vehicle body inclination angle, and the correction method thereof is as follows:
1. performing differential calculation and variance calculation processing of differential values on two-dimensional track point data obtained by a laser displacement sensor group
Data obtained by the three two-dimensional laser displacement sensors are integrated into the same coordinate system, and variance is calculated. Taking the laser displacement sensor 51 as an example, after the laser displacement sensor 51 acquires a set of track point data, the track point data includes track top characteristic point data (x 10 ,y 10 ),(x 11 ,y 11 )...(x 1n ,y 1n ). Then, the difference value y of the height direction coordinate data is obtained 11 -y 10 ，y 12 -y 11 ,…,y 1n -y 1(n-1) ＝Δy 10 ，Δy 11 ，…，Δy 1(n-1)
From which ten data deltay are selected 10 ，Δy 11 ，…，Δy 19 And calculates the variance value thereof, and then removes deltay 10 And add Δy 20 And obtaining the second group of ten data, continuously calculating the variance of the second group of ten data, calculating the variance of a plurality of groups of data according to the rule, and selecting the coordinate point of one group of data with the smallest variance value as the data of the top characteristic point of the rail surface.
2. Calculation of left-right inclination angle of vehicle body
Combining the rail surface top characteristic point data of the left rail 100 and the rail surface top characteristic point data of the right rail 200, fitting characteristic points in the two groups of rail surface top characteristic point data obtained in the process into a straight line by adopting a least square method to obtain a slope a of the straight line 1 And the linear equation is obtained as follows: y=a 1 x+a 0 From this slope, the vehicle body inclination angle can be derived: a=tan -1 a 1 。
3. Correcting errors caused by left and right inclination of the vehicle body and obtaining data after the first correction
And correcting the track data point errors according to the vehicle body inclination angle A. Error correction is performed on the abscissa and ordinate of the track point data by using the vehicle body inclination angle a, and then the left track 100, the right track 200 and the power supply track 300 are corrected according to a coordinate conversion formula x '=xcosa+ysina, y' =ycosa-xsna, and the corrected track point data obtained by correcting the left track 100 are respectively:
(x′ 10 ,y′ 10 )，(x′ 11 ,y′ 11 )，···，(x′ 1n ,y′ 1n )
4. correcting errors caused by the front-rear inclination of the vehicle body and obtaining data after the second correction
Referring to fig. 5, fig. 5 is a schematic diagram of track width dependence, taking the left track 100 as an example, the left track 100 includes a broadside 110, a narrow side 120, and a slot 130 between the broadside 110 and the narrow side 120, a first track width point is taken by moving the track top surface downwards by 2mm on the outer side of the broadside 110, a second track width point is taken by moving the track top surface downwards by 8mm on the inner side of the narrow side 120, and the horizontal distance between the first track width point and the second track width point is the track width d of the left track 100 1 。
The first track width point acquisition process comprises the following steps:
synthesizing the rail vertex data of the left rail 100 in the data after the first correction into a straight line by a least square method, and translating the straight line downwards by 2mm to obtain a straight line equation of y=k 1 x+b 1 +2, then the average value of the rail vertex data after the Y-coordinate is shifted down by 2mm is calculated:finding out first several ordinate and straight line from the track top point to the left point>Point y 'with minimum difference' 1k ，y′ 1(k+1) ，…，y′ 1(k+m) And 2 times of curve fitting is carried out on the point data, so that a curve can be obtained: y is a ＝b a2 x 2 +b a1 x+b a0 . Finally, the straight line y=k 1 x+b 1 +2 and curve y a ＝b a2 x 2 +b a1 x+b a0 Simultaneous solution to obtain the first track width point (x' 1a ,y′ 1a )。
The process of obtaining the second track width point is identical to that of the first track width point, and the straight line y=k is obtained successively 1 x+b 1 +8 and curve ya=b a2 x 2 +b a1 x+b a0 Then solving the straight line and the curve simultaneously to obtain a second track width point (X' 1b ，y′ 1b )。
The track width obtained at this time is the first corrected track width data, the track width d 1 Sum track width d 2 The track width data generated by eliminating errors generated by the left and right tilt angles of the vehicle body are all data in the track point data, so that correction of errors generated by the front and rear tilt angles of the vehicle body is still required. The distance between the first track width point and the second track width point is track width, d 12 Is of standard track width d 1 Is the first corrected rear track width, d, of the left track 100 2 Is the first corrected rear track width of the right track 200, the first corrected rear track width of the left track 100 and the first corrected rear track width of the right track 200 can be obtained from the first corrected track point data, and then the first corrected track point data can be passed through the indicationCalculating a front-rear inclination angle C of the vehicle body:
and correcting coordinate data of the three tracks according to the front-rear inclination angle C of the vehicle body to obtain final corrected data, wherein the final corrected data can ensure that the error of the actual contour data calculated in the next process is minimized.
After the final corrected data are obtained, step S13 is executed, and the processor generates actual geometric parameters such as track gauge, abrasion value, power supply track unevenness, center line deviation and the like according to the final corrected data, wherein the track gauge, the track width and the like are actual profile data of the groove type track.
Track gauge:
with reference to fig. 6, fig. 6 is a cross-sectional view of a grooved rail set. The gauge D is the distance between a first gauge feature point on the left rail 100 to a second gauge feature point on the right rail 200. The gauge feature point is positioned on the wide side of the groove type rail and near the groove side, and is positioned at the position of translating the rail top surface downwards by 14mm, and the linear y=k of the rail top surface 1 x+b 1 Translation 14mm down gives a straight line y=k 1 x+b 1 +14; then, the average value of the rail vertex data after the Y coordinate is shifted down by 14mm is calculated:finding out first several ordinate and straight line from the track top point to the left point>Point y 'with minimum difference' 1k ，y′ 1(k+1) ，…，y′ 1(k+m) And fitting these point data 2 times to obtain a straight line: y' a ＝k′ a x+b′ a . Finally, the straight line y=k 1 x+b 1 +14 and straight line y' a ＝k′ a x+b′ a Simultaneous solution to obtain a first gauge feature point (x' 1d ,y′ 1d ) Similarly, a second gage characteristic point (x 'for the right rail 20 is obtained' 2d ，y′ 2d ) From which it can be calculatedOut-groove track gauge d=x' 2d -x′ 1d 。
Abrasion value data:
referring to fig. 7, fig. 7 is a schematic diagram showing the relationship between wear values in the present embodiment. The processor compares the actual profile data with the standard profile data in the database, thereby obtaining the abrasion value data of the groove type rail.
The total abrasion of the groove-shaped rail comprises vertical abrasion and side abrasion, wherein the vertical abrasion and the side abrasion are respectively from a vertical abrasion point and a side abrasion point, the width of the broadside 110 of the groove-shaped rail is L1, and on the rail top surface, the point obtained by horizontally and outwards extending the broadside 110 from the edge of the side where the groove 130 is positioned by a distance L2 is the vertical abrasion point 141, wherein the length of L2 is 1/3 of the length of L1; the point obtained from translating the rail top surface of the broadside 110 down 10mm on the side of the groove 130 near the broadside is the side wear point 142.
The groove bottom 150 of the groove 130 is a non-abrasion area, and the groove bottom 150 of the final corrected data obtained after two corrections is overlapped with the groove bottom in the standard profile data, so that the difference between the vertical abrasion point 141 and the side abrasion point 142 in the final corrected data and the vertical abrasion point and the side abrasion point in the standard profile data can be compared, thereby obtaining the vertical abrasion data and the side abrasion data, and finally obtaining the abrasion value data.
Unevenness data and center line deviation data of the power supply rail:
the power supply rail unevenness comprises a first unevenness G1 and a second unevenness G2, wherein the first unevenness G1 is the relative position error between the power supply rail and the groove type rail, and the second unevenness G2 is the relative position error between the multi-section connected power supply rail connection sections. In the first item of unevenness G1, the height difference between the upper top surface of the power supply rail and the rail top surface of the groove rail is required to be 12mm±15mm, and the power supply rail unevenness data concerning the first item of unevenness G1 can be obtained by comparing the rail top surface data of the groove rail in the actual profile data obtained through error correction twice with the rail top surface data of the power supply rail.
The second item of unevenness G2 needs to compare two actual profile data obtained by a processor from two power supply rail connection sections, the laser displacement sensor respectively sends data acquisition for one time at two sides of the connection position of the two power supply rail connection sections according to pulse signals of the photoelectric encoder, and the power supply rail surface point data in the two actual profile data obtained after the acquisition and correction are compared, so that the power supply rail unevenness data about the second item of unevenness G2 can be generated.
Referring to fig. 3 and 6, two non-abrasion points 301 and 302 are provided at the upper ends of the two sides of the power supply rail 300, the center line between the non-abrasion points 301 and 302 is the actual center line of the power supply rail, and the center line deviation of the power supply rail is obtained by comparing the actual center line of the power supply rail with the center line of the track gauge D between the left rail 100 and the right rail 200.
After the step S21 is completed, step S22 is executed, and the processor generates track irregularity data according to the detection data obtained by the acceleration sensor.
The groove type track irregularity values comprise a height irregularity value and a track direction irregularity value, the photoelectric encoder sends a pulse signal, and the acceleration sensor sends a detection signal, and the acceleration sensor comprises a vertical acceleration detection function and a lateral acceleration detection function, so that the acceleration sensor can obtain vertical acceleration and lateral acceleration. And the processor performs secondary integration processing on the obtained vertical acceleration and the obtained transverse acceleration to obtain the height irregularity value and the track direction irregularity value of the groove track.
After step S31 is completed, step S32 is executed, and the processor combines the detection data obtained by the gyro sensor and the corrected data obtained in step S12 to generate level value data. The horizontal value data is the horizontal height difference data between the rail top surface of the left rail and the rail top surface of the right rail.
Referring to fig. 4 and 6, a straight line L3 connecting the left rail 100 and the right rail 200 has an inclination angle B with respect to the horizontal plane, and a vehicle body has an inclination angle a with respect to the straight line L3, and a vehicle body has an inclination angle Z with respect to the horizontal plane, so that it is possible to obtain: z=a+b.
The gyro sensor and the laser displacement sensor simultaneously emit detection signals while the photoelectric encoder transmits pulse signals, the processor generates ground tilt angle data about the tilt angle Z based on the angular velocity acquired by the gyro sensor, and the laser displacement sensor can generate corrected data about the tilt angle a based on the track point data, and the processor can generate the tilt angle B and level value data related to the tilt angle B based on the corrected data and the ground tilt angle data. The horizontal value is a horizontal height difference value h between the left rail gauge point and the right rail gauge point, and the horizontal height difference value h is obtained through calculation according to the gauge D and the inclination angle B: h=d×sinb.
And finishing the detection of the geometric parameters of the track after the step S13, the step S21 and the step S31 are finished.
The track geometric parameter detection vehicle is provided with a laser displacement sensor, an acceleration sensor and a gyroscope sensor, the laser displacement sensor can acquire profile point coordinate data of a cross section of a groove-shaped track buried in the ground, two laser displacement sensors on two sides obtain a top profile point to be fitted into a straight line, the straight line has a slope in coordinates obtained by combining the two laser displacement sensors, so that the inclination angle of a vehicle body relative to a track is known, and the profile point coordinate data of the groove-shaped track is converted again through a processor to realize track data correction. The track geometric parameter detection vehicle and the track geometric parameter detection method provided by the invention realize the data detection of the groove-shaped track, and simultaneously enable the detected and generated geometric parameter data to have higher accuracy through error correction.
Finally, it should be emphasized that the foregoing description is merely illustrative of the preferred embodiments of the invention, and that various changes and modifications can be made by those skilled in the art without departing from the spirit and principles of the invention, and any such modifications, equivalents, improvements, etc. are intended to be included within the scope of the invention.
Claims (9)
1. The track geometric parameter detection vehicle comprises a vehicle body, a track wheel set, a sensor group and a photoelectric encoder, wherein the track wheel set, the sensor group and the photoelectric encoder are arranged on the vehicle body, the sensor group comprises an acceleration sensor, the track wheel set comprises a left track wheel and a right track wheel, and the photoelectric encoder is arranged at a rotating shaft connected with the track wheel set;
the method is characterized in that:
the sensor group further comprises a laser displacement sensor group and a gyroscope sensor, and the laser displacement sensor group comprises three laser displacement sensors;
the left rail wheel and the right rail wheel are respectively provided with an acceleration sensor and a laser displacement sensor, and the center between the left rail wheel and the right rail wheel is provided with the laser displacement sensor;
the track geometric parameter detection vehicle further comprises a rotating device, wherein the rotating device comprises a fixed part, a connecting part and a rotating part which are sequentially connected, the connecting part can rotate along a first axis relative to the fixed part, the rotating part can rotate along a second axis relative to the connecting part, and the first axis and the second axis are mutually perpendicular;
the fixed part is connected with the vehicle body, and the rotating part is connected with the laser displacement sensor;
the rotating part comprises a triangular plate, fixing bolts are arranged at three corners of the triangular plate, the laser displacement sensor is fixed on the plate through the fixing bolts, and the detection direction of the laser displacement sensor can be adjusted by vertical incidence through the rotating device;
the fixed part and the connecting part and the rotating part are locked and rotated through threaded fit;
the track is a channel rail including a broadside, a narrow side, and a channel between the broadside and the narrow side.
2. The track geometry inspection vehicle of claim 1 wherein:
the track geometric parameter detection vehicle further comprises a road wheel set and a hydraulic device, wherein the road wheel set is arranged at the lower part of the vehicle body, the hydraulic device is connected between the track wheel set and the vehicle body, and the hydraulic device drives the track wheel set to move so that the horizontal position of the lowest point of the track wheel set is located below the horizontal position of the lowest point of the road wheel set.
3. The track geometry detection vehicle according to claim 1 or 2, characterized in that:
the track geometric parameter detection vehicle further comprises a cantilever and a detection beam, wherein the detection beam is connected to the vehicle body through the cantilever, and the detection beam is transversely arranged;
the sensor group is arranged on the detection beam.
4. The track geometric parameter detection method is characterized by comprising the following steps of: the method applies the track geometric parameter detection vehicle according to any one of claims 1 to 3 to detect track geometric parameter data;
the detection method comprises the following steps:
the laser displacement sensor group acquires track point data and sends the track point data to the processor;
the processor corrects errors generated by the inclination angle of the vehicle body according to the track point data to generate corrected data;
the processor generates actual geometry data from the corrected data.
5. The method for detecting geometrical parameters of a track according to claim 4, wherein:
the laser displacement sensor group acquires track point data and sends the track point data to the processor, and the detection method further comprises the following steps:
the photoelectric encoder sends out pulse signals, and the laser displacement sensor group obtains track point data according to the pulse signals.
6. The method for detecting geometrical parameters of a track according to claim 5, wherein:
after the photoelectric encoder sends out the pulse signal, the detection method further comprises the following steps:
and the acceleration sensor acquires acceleration data according to the pulse signals, and the processor generates irregularity data according to the acceleration data.
7. The method for detecting geometrical parameters of a track according to claim 5, wherein:
the processor corrects an error generated by a vehicle body inclination angle according to the track point data to generate corrected data, and the detection method further comprises:
the gyroscope sensor acquires the data of the ground inclination angle of the vehicle body relative to the ground according to the pulse signals, and the processor generates horizontal value data according to the corrected data and the ground inclination angle data.
8. The method for detecting geometrical parameters of a track according to claim 4, wherein:
the actual geometry data includes actual profile data, and the processor generates wear value data and centerline deviation data about the power supply rail by comparing the actual profile data to standard profile data.
9. The method for detecting geometrical parameters of a track according to claim 8, wherein:
the processor generates actual geometric parameter data according to the corrected data, and the detection method further comprises the following steps:
the processor generates power rail unevenness data from the actual profile data acquired twice.
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Families Citing this family (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108828068B (en) * | 2018-01-18 | 2021-05-25 | 武汉汉宁轨道交通技术有限公司 | Track surface wave abrasion and damage detection device and method |
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| CN110450814B (en) * | 2019-08-06 | 2020-12-22 | 中国铁建重工集团股份有限公司 | Track detection assembly |
| CN111307078A (en) * | 2020-02-21 | 2020-06-19 | 暨南大学 | Track irregularity detection method and system based on four-point chord measurement method |
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| CN113358053B (en) * | 2021-04-27 | 2023-02-24 | 中车青岛四方机车车辆股份有限公司 | Track irregularity detection and evaluation system and method, electronic equipment and track vehicle |
| CN113085948B (en) * | 2021-06-09 | 2021-10-19 | 成都国铁电气设备有限公司 | Track comprehensive detection system |
| CN113864385A (en) * | 2021-08-18 | 2021-12-31 | 北京强度环境研究所 | Acceleration sensor vibration damper and high-speed rail |
| CN114454914A (en) * | 2021-09-03 | 2022-05-10 | 北京大成国测科技有限公司 | Track data measuring method and device based on track detection vehicle and electronic equipment |
| CN113984109B (en) * | 2021-09-28 | 2022-08-16 | 北京大成国测科技有限公司 | Track detection data correction method and device and electronic equipment |
| CN114964046B (en) * | 2022-06-21 | 2023-06-02 | 湖南科天健光电技术有限公司 | Method, device, equipment and medium for measuring rail profile |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201261472Y (en) * | 2008-07-23 | 2009-06-24 | 成都唐源科技有限责任公司 | Vehicle mounted on-line detection device of subway third rail |
| JP2013006458A (en) * | 2011-06-22 | 2013-01-10 | Hitachi High-Technologies Corp | Inspection method and apparatus |
| CN103243621A (en) * | 2013-05-12 | 2013-08-14 | 中国十七冶集团有限公司 | Method for mounting integrated steel rail supporting frame for adjustment of groove type steel rails of tramcar |
| CN103863357A (en) * | 2014-03-21 | 2014-06-18 | 杭州海聚动力科技有限公司 | Rail transit contact track measuring device and measuring method |
| CN207274714U (en) * | 2017-08-11 | 2018-04-27 | 暨南大学 | Orbital data detects car |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8081320B2 (en) * | 2004-06-30 | 2011-12-20 | Georgetown Rail Equipment Company | Tilt correction system and method for rail seat abrasion |
| US7659972B2 (en) * | 2007-08-22 | 2010-02-09 | Kld Labs, Inc. | Rail measurement system |
-
2017
- 2017-08-11 CN CN201710685110.XA patent/CN107380204B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201261472Y (en) * | 2008-07-23 | 2009-06-24 | 成都唐源科技有限责任公司 | Vehicle mounted on-line detection device of subway third rail |
| JP2013006458A (en) * | 2011-06-22 | 2013-01-10 | Hitachi High-Technologies Corp | Inspection method and apparatus |
| CN103243621A (en) * | 2013-05-12 | 2013-08-14 | 中国十七冶集团有限公司 | Method for mounting integrated steel rail supporting frame for adjustment of groove type steel rails of tramcar |
| CN103863357A (en) * | 2014-03-21 | 2014-06-18 | 杭州海聚动力科技有限公司 | Rail transit contact track measuring device and measuring method |
| CN207274714U (en) * | 2017-08-11 | 2018-04-27 | 暨南大学 | Orbital data detects car |
Non-Patent Citations (1)
| Title |
|---|
| 城轨车辆车载自动轨道检测装置;刘家栋等;《电力机车与城轨车辆》;20141120;第37卷(第6期);全文 * |
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|---|---|
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