CN116691767A - Rail transit wheel tread damage detection method - Google Patents
Rail transit wheel tread damage detection method Download PDFInfo
- Publication number
- CN116691767A CN116691767A CN202310931678.0A CN202310931678A CN116691767A CN 116691767 A CN116691767 A CN 116691767A CN 202310931678 A CN202310931678 A CN 202310931678A CN 116691767 A CN116691767 A CN 116691767A
- Authority
- CN
- China
- Prior art keywords
- rail
- tread
- wheel
- detection position
- detection
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 128
- 230000006378 damage Effects 0.000 title claims abstract description 57
- 229910000831 Steel Inorganic materials 0.000 claims abstract description 33
- 239000010959 steel Substances 0.000 claims abstract description 33
- 238000000034 method Methods 0.000 claims abstract description 31
- 241001669679 Eleotris Species 0.000 claims abstract description 18
- 230000007547 defect Effects 0.000 claims description 15
- 230000008569 process Effects 0.000 claims description 5
- 238000003825 pressing Methods 0.000 claims description 4
- 230000001681 protective effect Effects 0.000 claims description 3
- 238000010276 construction Methods 0.000 abstract description 16
- 238000005303 weighing Methods 0.000 abstract description 15
- 238000009434 installation Methods 0.000 abstract description 9
- 238000010008 shearing Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 230000004048 modification Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000006978 adaptation Effects 0.000 description 2
- 238000000418 atomic force spectrum Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 239000002131 composite material Substances 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- 238000005299 abrasion Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000003139 buffering effect Effects 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 229920001971 elastomer Polymers 0.000 description 1
- 239000000806 elastomer Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000004080 punching Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Classifications
-
- 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
- B61K9/12—Measuring or surveying wheel-rims
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
Landscapes
- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Force Measurement Appropriate To Specific Purposes (AREA)
Abstract
The invention discloses a method for detecting damage to a tread of a wheel of a rail transit, and belongs to the field of rail transit. The steel rails at two sides in the detection area are detected according to the same method, two detection positions are arranged on the rail web of a section of steel rail in each two adjacent sleepers for the steel rail at one side, and a shear sensor is arranged at each detection position; and the shear sensor group bridge of the Nth detection position and the (n+1) th detection position, the shear sensor group bridge of the Nth detection position and the (n+3) th detection position, and each shear sensor is connected with the processor. And the specific data processing scheme of the invention can realize the detection of the tread damage of the wheels. The invention does not use a weighing sensor, has simple structure and convenient installation, does not need to reform the existing roadbed, sleeper or fastener, can finish projects which cannot be finished in the prior art, such as high-speed rails, subways and the like, are sensitive to reform and limited in construction time, and reduces the construction time, cost and potential safety hazards caused by construction.
Description
Technical Field
The invention relates to the field of rail transit, in particular to a method for detecting damage to a tread of a wheel of rail transit.
Background
The interaction between the wheels and the rails directly affects the running safety of railways, the abrasion and maintenance of wheel rails, continuous rail tracks are installed in a large number in the railway, subway and urban rail industries at present, and the interaction force between the wheels and the continuous rail tracks is measured through a rail weighing device.
Specifically, the detection area and the circuit are mechanically segmented through the shear sensor arranged on the steel rail, and the weighing sensor arranged in the detection area is matched with the shear sensor to eliminate the mechanical influence of the circuit on the detection area through the steel rail, so that weighing is completed. However, this method requires the cooperation of two sensors, in particular weighing cells, the elastomer of which requires a certain installation space and therefore has a minimum limit on its external dimensions.
In the installation of the weighing sensor, the original sleeper, ballast bed or fastener and the like are required to be modified. The construction workload is large, the process is complex (such as crushing the original structure and pouring a new structure), and the period is long, so that potential safety hazards such as construction and operation are brought. The detection mode is not suitable for occasions such as high-speed railway lines, motor train lines, subway lines and the like. If the original structure is modified in the occasions, the skylight period (the time for construction on the way) is short, for example, the skylight period of a high-speed rail is indefinite when the subway is usually 3 hours per day. Moreover, the prior art can only realize weighing, and cannot detect whether the tread of the wheel has damage or not.
Disclosure of Invention
The invention provides a method for detecting the damage of the tread of a rail transit wheel, which has the advantages of simple structure, convenient installation and reduced construction time, cost and potential safety hazards caused by construction.
The technical scheme provided by the invention is as follows:
the method for detecting the damage of the tread of the wheel of the rail transit comprises the steps of:
two detection positions are arranged on the rail waist of a section of rail in each two adjacent sleepers for the rail on one side of the detection area, a shear sensor is arranged on each detection position, and each shear sensor is connected with a processor; a shear sensor group bridge of an nth detection position and an n+1th detection position, and a shear sensor group bridge of an nth detection position and an n+3rd detection position in order of detection positions, wherein n=1, 3,5,7, …;
for the steel rail on one side, acquiring waveforms of the shear force sensors at all detection positions of the wheels passing through the detection area through a processor, wherein the horizontal axis of the waveforms is time, and the vertical axis of the waveforms is an output value of the shear force sensors;
adding the waveforms of the shear force sensors at the Nth detection position and the (n+3) th detection position to obtain a synthesized waveform;
based on the horizontal axis, displaying each synthesized waveform in the same coordinate system according to the time sequence to obtain a waveform graph;
and performing curve fitting on the top straight part of each synthesized waveform based on the waveform graph, and determining the damage type of the tread of the wheel according to the shape characteristics of the fitted curve obtained by fitting.
Further, the curve fitting is performed on the top straight part of each synthesized waveform based on the waveform graph, and the damage type of the tread of the wheel is determined according to the shape characteristics of the fitted curve obtained by fitting, including:
comparing the shape characteristics of the fitting curve with curve characteristics of various damage types obtained in advance, and determining the damage type of the tread of the wheel according to the similarity;
wherein, the curve characteristics of various damage types are obtained in advance through the following processes:
obtaining a fitting curve of wheels without tread defects and wheels with tread of various damage types passing through a detection area in advance;
the curve characteristics of various damage types are determined in advance according to the difference between the fitting curve of the tread wheels with various damage types passing through the detection area and the fitting curve of the tread wheels without tread defects passing through the detection area.
Further, the method further comprises:
acquiring a fitting curve of a shear sensor at a selected detection position when each wheel pair of the train passes through the selected detection position by taking the selected detection position as a reference;
the fitting curves of all the wheel pairs are displayed under the same coordinate system according to the time sequence by taking the transverse axis as a reference, so that a continuous waveform data set is obtained;
when the tread of a certain wheel is damaged, positioning the serial number of the fitting curve on a continuous waveform data set to obtain the serial number of the wheel pair;
the train number is acquired through shooting identification by the set train number acquisition system, and the damaged wheel pair is obtained through the train number and the wheel pair serial number positioning;
and according to the corresponding relation of the shear sensors of the steel rails at the two sides of the same detection position, positioning to obtain the left wheel or the right wheel of the damaged wheel pair, and positioning the damaged wheel.
Further, the detection area is located at a straight section of the steel rail, the length of the detection area is larger than the circumference of the wheel, the distance between the detection position closest to the sleeper and the sleeper is not smaller than half of the height of the steel rail, and the distance between two adjacent detection positions in two adjacent sleepers is 200-300 mm.
Further, each detection position is provided with two shear force sensors, and the two shear force sensors at the same detection position are symmetrically arranged at two sides of the detection position of the rail web.
Further, the shear sensor is mounted on the web of the rail by a mounting bracket, wherein:
the mounting bracket comprises two symmetrical bracket units, the two bracket units are symmetrically arranged on two sides of the steel rail, the upper part of each bracket unit is used for tightly pressing the shear sensor on the side face of the rail web of the steel rail through a first group of bolts, and the lower parts of the two bracket units are connected and fastened together through a second group of bolts.
Further, the support unit comprises a sensor mounting part and a support unit connecting part, wherein the sensor mounting part is positioned at a set distance outside the rail web of the steel rail, the support unit connecting part is positioned below the sensor mounting part, and the support unit connecting part extends from the bottom of the steel rail to the inner side of the steel rail;
and the sensor mounting part of each bracket unit is used for pressing the shear sensor on the rail web side surface of the steel rail through the first group of bolts, and the bracket unit connecting parts of the two bracket units are connected and fastened together through the second group of bolts.
Further, a disc spring gasket is arranged between the first group of bolts and the shear sensor, and a protective cover is arranged outside the mounting bracket.
Further, the shape of the inner side of the lower part of the bracket unit corresponds to the shape of the lower part of the rail.
The invention has the following beneficial effects:
compared with the prior art, the invention does not use a weighing sensor, and only needs to install a shear sensor on the rail between every two sleepers, preferably the middle part of the rail web, in the detection area, and 2 groups of shear sensors are installed between two adjacent sleepers. The shearing force sensors are arranged continuously to obtain the length of a required detection area, the continuous shearing force sensors are arranged, and the specific bridge combination scheme and the data processing scheme of the invention are carried out, so that the detection of the tread damage of the wheel can be realized.
The invention does not use a weighing sensor, has simple structure and convenient installation, does not need to reform the existing roadbed, sleeper or fastener, can finish projects which cannot be finished in the prior art, such as high-speed rails, subways and the like, are sensitive to reform and limit the construction time (the skylight period is short, and is usually 3 hours per day), and reduces the construction time, the cost and the potential safety hazard brought by construction.
Drawings
FIG. 1 is a side view of a structure corresponding to a method for detecting tread damage of a rail transit wheel of the present invention;
FIG. 2 is a plan view of a structure corresponding to the method for detecting tread damage of a rail transit wheel according to the present invention;
FIG. 3 is a schematic view of a shear sensor bridge;
FIG. 4 is a sectional view of the installation of a shear force sensor;
FIG. 5 is an installed side view of a shear force sensor;
FIG. 6 is a waveform example diagram of a shear force sensor at the 1 st detection position;
FIG. 7 is a waveform example diagram of a shear force sensor at the 4 th detection position;
FIG. 8 is an exemplary plot of the summed synthesized waveforms of FIGS. 6 and 7;
FIG. 9 is a waveform diagram of the composition of each composite waveform;
FIG. 10 is a schematic diagram of a waveform graph after straight line fitting;
FIG. 11 is a schematic diagram of a waveform graph after curve fitting;
FIG. 12 is a fitted curve corresponding to wheel flat defects;
fig. 13 is a fitted curve corresponding to a polygonal defect of a wheel.
Detailed Description
In order to make the technical problems, technical solutions and advantages to be solved more apparent, the following detailed description will be given with reference to the accompanying drawings and specific embodiments.
The invention provides a method for detecting tread damage of wheels of rail transit, which is shown in figures 1-5, wherein steel rails 1 at two sides in a detection area are detected according to the same method, and the method comprises the following steps:
s1: for the steel rail 1 at one side of the detection area, two detection positions 5 are respectively arranged on the rail web 4 of one section of steel rail 1 in each two adjacent sleepers 2, a shear force sensor 3 is respectively arranged on each detection position 5, and each shear force sensor 3 is connected with a processor; in order of detection positions 5, the nth detection position 5 bridges the group of shear sensors 3 of the n+1th detection position 5, and the nth detection position 5 bridges the group of shear sensors 3 of the n+3th detection position 5, where n=1, 3,5,7, ….
Namely a shear sensor group bridge of the 1 st detection position and the 2 nd detection position, a shear sensor group bridge of the 3 rd detection position and the 4 th detection position, and the like; namely a shear sensor group bridge at the 1 st detection position and the 4 th detection position, a shear sensor group bridge at the 3 rd detection position and the 6 th detection position and the like, so as to obtain continuous wheel weight values and continuous detection of damaged non-blind areas of the wheels. And acquiring waveforms of the vehicle load in the passing detection area, and eliminating the influence of the sleeper in the detection area by fitting a plurality of acquired waveforms, so as to obtain an accurate wheel weight detection value (load force value).
S2: for one of the rails, the processor acquires waveforms of the shear force sensors at all detection positions of the wheels passing through the detection area, wherein the horizontal axis of the waveforms is time, and the vertical axis of the waveforms is the output value of the shear force sensors.
S3: and adding the waveforms of the shear force sensors at the N detection position and the (n+3) th detection position to obtain a synthesized waveform.
For example, when n=1, the waveform of the shear sensor at the 1 st detection position is shown in fig. 6, the waveform of the shear sensor at the 4 th detection position is shown in fig. 7, and the combined waveform of the two is shown in fig. 8. For n=3, 5,7, …, a similar series of composite waveforms can be obtained.
S4: and displaying the synthesized waveforms in the same coordinate system according to the time sequence by taking the horizontal axis as a reference to obtain a waveform graph.
Exemplary waveform profiles are shown in fig. 9.
S5: and (3) performing curve fitting on the top straight part of each synthesized waveform based on the waveform graph, and determining the damage type of the tread of the wheel according to the shape characteristics of the fitted curve obtained by fitting.
Once the wheel is damaged, mechanical characteristics such as vibration of load force can be reflected on a waveform graph, and tread damage can be detected based on the characteristics of the load force.
For example, as shown in fig. 11, when the tread of the wheel is damaged, the instantaneous rotation center changes when the wheel rotates. This change causes the wheel to impact the rail vertically, thereby creating an impact load (as shown in fig. 11). The characteristics of the impact load are analyzed, and the damage type of the tread of the wheel can be judged in sequence.
In the prior art, the original sleeper needs to be removed and replaced by a sleeper capable of being provided with a weighing sensor, if the sleeper is an integral ballast bed or a track slab, the sleeper needs to be partially modified, the original sleeper is removed, the sleeper is modified into a sleeper which can be suitable for being provided with a vertical force sensor, the construction amount is large, the period is long, and especially the problems of maintenance of new filling materials, support in a transition period and the like need to be coordinated in the modification process, so that the construction period is generally more than 2 months, and unknown potential safety hazards are brought due to the change of the original structure.
Compared with the prior art, the invention does not use a weighing sensor, and only needs to install a shear sensor on the rail between every two sleepers, preferably the middle part of the rail web, in the detection area, and 2 groups of shear sensors are installed between two adjacent sleepers. The shearing force sensors are arranged continuously to obtain the required length of the detection area, the continuous shearing force sensors are arranged, and the specific bridge combination scheme and the data processing scheme of the invention are carried out, so that the waveform of each wheel rotating for one circle can be obtained. And performing specific treatment according to the waveform to finish detection of tread damage.
The invention does not use a weighing sensor, has simple structure and convenient installation, does not need to reform the existing roadbed, sleeper or fastener, can finish projects which cannot be finished in the prior art, such as high-speed rails, subways and the like, are sensitive to reform and limit the construction time (the skylight period is short, and is usually 3 hours per day), and reduces the construction time, the cost and the potential safety hazard brought by construction.
Specifically, S5 includes:
and comparing the shape characteristics of the fitting curve with curve characteristics of various damage types obtained in advance, and determining the damage type of the tread of the wheel according to the similarity.
Wherein, the curve characteristics of various damage types are obtained in advance through the following processes:
1. the method comprises the steps of obtaining a fitting curve of wheels without tread defects and wheels with tread of various damage types passing through a detection zone in advance.
Firstly, collecting a plurality of groups of shear data of wheels without tread defects passing through a detection area under different speeds, carrying out statistical analysis on the shear data, and analyzing the wheel track force curve characteristics of the wheels without tread defects.
Then collecting shearing force data of a plurality of groups of certain tread injuries, such as polygonal defects, wheel flat defects and the like; and carrying out statistical analysis on the shear data to analyze the wheel rail force curve characteristics of the wheel with the damaged tread. Fig. 12 and 13 show examples of fitted curves of wheel flat defects and polygonal defects, respectively.
2. The curve characteristics of various damage types are determined in advance according to the difference between the fitting curve of the tread wheels with various damage types passing through the detection area and the fitting curve of the tread wheels without tread defects passing through the detection area.
Namely, analyzing the difference characteristics of the two curves, and extracting the characteristics as the basis of defect judgment, namely, the curve characteristics of the damage type. The above operations are performed on the currently known types of tread damage of the wheels, and the judging conditions of each tread damage are determined.
After curve characteristics of each damage type are obtained in advance, when detection is carried out, the shape characteristics of the actually obtained fitting curve and the curve characteristics of the damage of the wheel tread are compared and analyzed, the similarity of the geometric shapes of the fitting curve and the curve characteristics of the damage are analyzed, and the accuracy of the damage is determined. If the accuracy is greater than 90% (settable), it is defined as such damage.
As an improvement of the embodiment of the present invention, the method further includes:
s6: and taking the selected detection position as a reference, acquiring a fitting curve of the shear sensor at the selected detection position when each wheel pair of the train passes through the selected detection position.
For example, a shear sensor at the 1 st detection position of the detection area in the train traveling direction can be generally selected as a data acquisition source for wheel alignment.
S7: and displaying the fitting curves of the wheel pairs in the same coordinate system according to the time sequence by taking the transverse axis as a reference to obtain a continuous waveform data set.
When a train passes through the shear force sensor at the detection position, the shear force sensor continuously acquires the wheel rail force waveform of each wheel pair passing through the shear force sensor; the waveforms are arranged in a time-axis order in the acquired waveform dataset.
S8: when the tread of a certain wheel is damaged, the serial number of the fitting curve is positioned on the continuous waveform data set, and the serial number of the wheel pair is obtained.
S9: through the train number acquisition system that sets up, the identification of shooing acquires the train number, and the wheel pair that has the damage is obtained through train number and wheel pair serial number location.
The train number acquisition system is generally installed behind the detection area, photographs the train, and recognizes the train number through an algorithm.
S10: and according to the corresponding relation of the shear sensors of the steel rails at the two sides of the same detection position, positioning to obtain the left wheel or the right wheel of the damaged wheel pair, and positioning the damaged wheel.
The same detection position corresponds to two steel rails, namely to two groups of shear force sensors, and according to the corresponding relation between the fitting curve of the damaged tread and the shear force sensors of the two steel rails, the left wheel or the right wheel of the wheel pair can be obtained, so that the damaged wheels are positioned.
The detection area is positioned on the straight section of the steel rail, the length of the detection area is larger than the circumference of the wheel, the wheel can be completely detected, and the detection blind area is eliminated. The distance between the nearest detection position from the sleeper and the sleeper is not less than half of the height of the steel rail, and the distance between two adjacent detection positions in two adjacent sleepers is 200-300 mm, preferably 270mm.
Each detection position is provided with two shear force sensors, and the two shear force sensors at the same detection position are symmetrically arranged at two sides of the detection position of the rail web.
For example, in the detection area, 2 pairs of H-shaped shear force sensors are arranged on a single-side steel rail between every two sleepers. And a shear force sensor is respectively arranged at the same transverse cutting positions on two sides of the single steel rail, and the 2 shear force sensors form 1 pair of shear force sensors. The other side rail is provided with a shear sensor in the same way.
The aforementioned shear sensor is mounted on the web 4 of the rail 1 by means of a mounting bracket 6, wherein:
the mounting bracket 6 comprises two symmetrical bracket units 7 and 8, the two bracket units 7 and 8 are symmetrically arranged on two sides of the steel rail 1, the upper part of each bracket unit 7 or 8 compresses the shear sensor 3 on the side face of the rail web 4 of the steel rail 1 through a first group of bolts 11, and the lower parts of the two bracket units 7 and 8 are connected and fastened together through a second group of bolts 12.
Specifically, each of the bracket units 7 or 8 includes a sensor mounting portion 9 and a bracket unit connecting portion 10, the sensor mounting portion 9 is located at a set distance outside the web 4 of the rail 1, the bracket unit connecting portion 10 is located below the sensor mounting portion 9, and the bracket unit connecting portion 10 extends from the bottom of the rail 1 toward the inside of the rail 1.
The shear sensor 3 is pressed against the web 4 side of the rail 1 by a first set of bolts 11 on the sensor mounting 9 of each bracket unit 7 or 8, and the bracket unit connections 10 of the two bracket units 7, 8 are fastened together by a second set of bolts 12.
The shape of the inner side of the lower part of the bracket unit 7 or 8 corresponds to the shape of the lower part of the rail 1, and the inner side of the lower part of the bracket unit 7 or 8 is clamped on the lower part of the rail 1 when the bracket unit is installed.
According to the invention, the shearing force sensor 3 is tightly pressed on the side surface of the rail web 4 in a symmetrical mode of inwards clamping the two bracket units 7 and 8 without damaging the original rail such as punching, so that the potential safety hazard to the rail is reduced.
During installation, only the sensor is required to be installed on the rail through bolts and the fixture, and the sensor wire is led into the electric cabinet beside the rail, so that equipment installation is completed. Plus commissioning time, typically within 15 hours, a project can be completed for 5 days with a 3 hour daily skylight period.
A disc spring gasket 13 is arranged between the first group of bolts 11 and the shear sensor 3 for buffering, and a protective cover 14 is arranged outside the mounting bracket 6 for protecting the internal structure.
The invention can also detect the track load to realize weighing, and the method specifically comprises the following steps:
s11: and fitting the top straight part of each synthesized waveform into a straight line based on the waveform graph, and determining the load force according to the fitted straight line to finish weighing.
Illustratively, the fitting is followed by the fitting shown in FIG. 10, which results in a continuous detection zone from the 1 st detection position to the last shear detection position. In fig. 10, the horizontal axis represents time, the vertical axis represents shear force, and the shear force corresponding to the fitted straight line represents load force, so that weighing is realized.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the present invention.
Claims (9)
1. The method for detecting the damage of the tread of the wheel of the rail transit is characterized in that steel rails at two sides in a detection area are detected according to the same method, and the method comprises the following steps:
two detection positions are arranged on the rail waist of a section of rail in each two adjacent sleepers for the rail on one side of the detection area, a shear sensor is arranged on each detection position, and each shear sensor is connected with a processor; a shear sensor group bridge of an nth detection position and an n+1th detection position, and a shear sensor group bridge of an nth detection position and an n+3rd detection position in order of detection positions, wherein n=1, 3,5,7, …;
for the steel rail on one side, acquiring waveforms of the shear force sensors at all detection positions of the wheels passing through the detection area through a processor, wherein the horizontal axis of the waveforms is time, and the vertical axis of the waveforms is an output value of the shear force sensors;
adding the waveforms of the shear force sensors at the Nth detection position and the (n+3) th detection position to obtain a synthesized waveform;
based on the horizontal axis, displaying each synthesized waveform in the same coordinate system according to the time sequence to obtain a waveform graph;
and performing curve fitting on the top straight part of each synthesized waveform based on the waveform graph, and determining the damage type of the tread of the wheel according to the shape characteristics of the fitted curve obtained by fitting.
2. The method for detecting damage to a tread of a rail transit vehicle according to claim 1, wherein the step of performing curve fitting on a top straight portion of each synthesized waveform based on the waveform graph, and determining the damage type of the tread according to the shape characteristics of the fitted curve obtained by the fitting, comprises:
comparing the shape characteristics of the fitting curve with curve characteristics of various damage types obtained in advance, and determining the damage type of the tread of the wheel according to the similarity;
wherein, the curve characteristics of various damage types are obtained in advance through the following processes:
obtaining a fitting curve of wheels without tread defects and wheels with tread of various damage types passing through a detection area in advance;
the curve characteristics of various damage types are determined in advance according to the difference between the fitting curve of the tread wheels with various damage types passing through the detection area and the fitting curve of the tread wheels without tread defects passing through the detection area.
3. The method for detecting tread damage to a rail transit wheel as in claim 2, further comprising:
acquiring a fitting curve of a shear sensor at a selected detection position when each wheel pair of the train passes through the selected detection position by taking the selected detection position as a reference;
the fitting curves of all the wheel pairs are displayed under the same coordinate system according to the time sequence by taking the transverse axis as a reference, so that a continuous waveform data set is obtained;
when the tread of a certain wheel is damaged, positioning the serial number of the fitting curve on a continuous waveform data set to obtain the serial number of the wheel pair;
the train number is acquired through shooting identification by the set train number acquisition system, and the damaged wheel pair is obtained through the train number and the wheel pair serial number positioning;
and according to the corresponding relation of the shear sensors of the steel rails at the two sides of the same detection position, positioning to obtain the left wheel or the right wheel of the damaged wheel pair, and positioning the damaged wheel.
4. A method of detecting tread damage to a rail transit wheel according to any one of claims 1 to 3 wherein the detection zone is located in a straight section of the rail, the length of the detection zone is greater than the circumference of the wheel, the spacing between the nearest detection location to the sleeper and the sleeper is not less than half the height of the rail, and the spacing between two adjacent detection locations in two adjacent sleepers is in the range of 200 to 300mm.
5. The method for detecting the tread damage of the rail transit wheels according to claim 4, wherein two shear sensors are arranged at each detection position, and the two shear sensors at the same detection position are symmetrically arranged at two sides of the detection position of the rail web.
6. The method for detecting tread damage to a rail transit wheel as in claim 5, wherein the shear sensor is mounted to a web of the rail by a mounting bracket, wherein:
the mounting bracket comprises two symmetrical bracket units, the two bracket units are symmetrically arranged on two sides of the steel rail, the upper part of each bracket unit is used for tightly pressing the shear sensor on the side face of the rail web of the steel rail through a first group of bolts, and the lower parts of the two bracket units are connected and fastened together through a second group of bolts.
7. The method for detecting damage to a tread of a rail transit wheel according to claim 6, wherein the bracket unit includes a sensor mounting portion and a bracket unit connecting portion, the sensor mounting portion is located at a set distance outside a web of the rail, the bracket unit connecting portion is located below the sensor mounting portion, and the bracket unit connecting portion extends from the rail bottom toward the rail inside;
and the sensor mounting part of each bracket unit is used for pressing the shear sensor on the rail web side surface of the steel rail through the first group of bolts, and the bracket unit connecting parts of the two bracket units are connected and fastened together through the second group of bolts.
8. The method for detecting damage to a tread of a rail transit wheel according to claim 7, wherein a disc spring washer is disposed between the first set of bolts and the shear sensor, and a protective cover is disposed outside the mounting bracket.
9. The method for detecting damage to wheels of rail transit as recited in claim 7, wherein a shape of an inner side of a lower portion of the bracket unit corresponds to a shape of a lower portion of the rail.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310931678.0A CN116691767A (en) | 2023-07-27 | 2023-07-27 | Rail transit wheel tread damage detection method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310931678.0A CN116691767A (en) | 2023-07-27 | 2023-07-27 | Rail transit wheel tread damage detection method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116691767A true CN116691767A (en) | 2023-09-05 |
Family
ID=87827950
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310931678.0A Pending CN116691767A (en) | 2023-07-27 | 2023-07-27 | Rail transit wheel tread damage detection method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116691767A (en) |
-
2023
- 2023-07-27 CN CN202310931678.0A patent/CN116691767A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110658005B (en) | Method for identifying rail corrugation diseases based on vehicle body acceleration | |
| EP0204817B1 (en) | Wheel load measurement | |
| US6662728B2 (en) | Machine and method for treating a track | |
| CN108515984B (en) | Wheel damage detection method and device | |
| CN101376392B (en) | Vehicle axle counting method based on steel rail deformation / stress parameters | |
| CN113085948B (en) | Track comprehensive detection system | |
| JPH09315304A (en) | Detecting device for unfastening of rail and detecting method | |
| CN106809247A (en) | A kind of vehicle-mounted automatic track detection device of city rail vehicle | |
| CN101377433B (en) | Method for measuring vehicle weight based on steel rail deformation / stress parameters | |
| CN112883997B (en) | Rail transit fastener detection system and detection method | |
| CN110936978B (en) | Ballastless track interlayer gap measuring method and device based on measuring trolley | |
| Real Herráiz et al. | Development of a system to obtain vertical track geometry measuring axle-box accelerations from in-service trains | |
| CN104477209A (en) | Railway locomotive vehicle wheel online scratch automatic detection system and method | |
| Vinkó et al. | Experimental investigation on condition monitoring opportunities of tramway tracks | |
| CN109855771B (en) | Method for detecting temperature based on vertical acceleration power spectrum density of steel rail | |
| CN116691767A (en) | Rail transit wheel tread damage detection method | |
| CN205320146U (en) | 3D scanner of other facility of railway rail | |
| CN116952347A (en) | Track load detection method | |
| CN116773070A (en) | Track load detection system | |
| Bocz et al. | A practical approach to tramway track condition monitoring: vertical track defects detection and identification using time-frequency processing technique | |
| Sawadisavi et al. | Machine-vision inspection of railroad track | |
| CN1703610A (en) | Device and method for monitoring the state of the sub-structure of fixed tracks | |
| CN111307191A (en) | Sound barrier bolt looseness rapid detection method | |
| CN114348054B (en) | Railway switch disease monitoring method, device and system | |
| CN110346601A (en) | Prefabricated railway roadbed attitude monitoring system and monitoring method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |