Wheelset tread polygon detection method and system

Abstract

The application provides a wheel set tread polygon detection method and system, comprising: S1, collecting the tread radial runout data of a train wheel set; S2, extracting the wheel set surface point cloud data corresponding to the wheel set tread radial runout data; S3, in a rectangular coordinate system, extracting the Z data of a circular section 70mm away from the inner side surface of the wheel in the X direction, which is the wheel set tread nominal rolling circle; S4, extracting the wheel set tread image; S5, based on the wheel set tread image and the wheel set tread nominal rolling circle, generating a wheel set tread three-dimensional point cloud diagram, a wheel set tread circular coordinate diagram and a wheel set tread polar coordinate diagram; S6, based on the wheel set tread circular coordinate diagram and the wheel set tread polar coordinate diagram, flattening the wheel set tread three-dimensional point cloud diagram to generate a wheel set tread defect area. Through the cooperation of the laser displacement sensor unit and the data processing unit, the problem that the existing wheel set tread polygon detection method is inconvenient to detect and the reliability of the detection result is low is solved, and the effect of conveniently and accurately detecting the wheel set tread polygon can be achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of rail vehicle detection, and in particular to a wheel set tread polygon detection method and system. BACKGROUND

[0002] The wheel is a key part related to the safety of train operation, which transmits the load of the vehicle to the rail and rotates on the rail to complete the operation of the train, and is the final force receiving component of the train. During the long operation of the railway vehicle, uneven wear of the wheel tread will cause the wheel to be out of round, and the wheel out of round will cause the front and rear wheels of the vehicle to be prone to high-frequency wheel-rail impact vibration, causing the vibration of the axle box and other connecting parts to intensify, and the tread to appear surface defect quality problems such as wear out of limit, scratch, peeling, and bruise. These problems may directly lead to derailment accidents and affect the safety of train operation. Therefore, it is necessary to conduct daily dynamic detection on the wheel tread to ensure the safety of train operation.

[0003] A series of researches have been carried out on the principle and method of wheel polygon measurement at home and abroad. For example, the device for automatically measuring the wheel set by using the laser non-contact measurement method is widely used, but this type of device is only suitable for use after the wheel set is disassembled and is completed on a special detection equipment. At present, during the wheel set maintenance operation, the measuring tools such as the detector, the inner distance ruler, the wheel diameter ruler, and the tread inspection instrument are used manually. Due to the limitation of the detection method and accuracy, these measuring tools cannot distinguish the subtle changes of the wheel polygon, and cannot completely eliminate the safety hazards.

[0004] In summary, the existing wheel set tread polygon detection method has the problems of inconvenient detection and low reliability of detection results. SUMMARY

[0005] The purpose of the present application is to provide a wheel set tread polygon detection method and system, which solves the problems of inconvenient detection and low reliability of detection results of the existing wheel set tread polygon detection method, and can conveniently and accurately detect the wheel set tread polygon.

[0006] To achieve the above-mentioned purpose of the application, the technical scheme adopted by the present application is a wheel set tread polygon detection method, comprising the following steps: step S1: collecting the tread radial runout data of the train wheel set; S2: extracting the wheel set surface point cloud data corresponding to the wheel set tread polygon data; S3: in the rectangular coordinate system, extracting the Z data of the circular section at a distance of 70mm from the inner side surface of the wheel, which is the nominal rolling circle of the wheel set tread; S4: extracting the wheel set tread image; S5: based on the wheel set tread image and the wheel set tread nominal rolling circle, generating a wheel set tread three-dimensional point cloud graph, a wheel set tread circular coordinate graph, and a wheel set tread polar coordinate graph; and S6: based on the wheel set tread circular coordinate graph and the wheel set tread polar coordinate graph, flattening the wheel set tread three-dimensional point cloud graph to generate a wheel set defect area.

[0007] Optionally, the S1 comprises: a laser displacement sensor, an encoder, a single-chip microcomputer, a second Bluetooth, and the laser displacement sensor, the encoder, the single-chip microcomputer, and the second Bluetooth are fixed on the permanent magnet relying piece, the permanent magnet relying piece is adsorbed on the steel rail, and the encoder is closely attached to the wheel tread.

[0008] Optionally, the S2 comprises: obtaining the radial jumping data of the rotating wheel tread, the distance difference of the laser displacement sensor to the wheel tread, and constructing the mapping relationship between the wheel tread polygon data and the wheel surface point cloud data.

[0009] Optionally, the S5 comprises: a wheel tread three-dimensional point cloud graph, the X axis is the tread transverse coordinate, the Y axis is the wheel circumference direction, that is, the sampling interval of the encoder, and the Z axis direction is the distance from the tread contour to the laser displacement sensor.

[0010] Optionally, the S5 comprises: a wheel tread three-dimensional point cloud graph, the X axis is the tread transverse coordinate, the Y axis is the wheel circumference direction, that is, the sampling interval of the encoder, and the Z axis direction is the distance from the tread contour to the laser displacement sensor.

[0011] Optionally, the S5 comprises: a wheel tread three-dimensional point cloud graph, the X axis is the tread transverse coordinate, the Y axis is the wheel circumference direction, that is, the sampling interval of the encoder, and the Z axis direction is the distance from the tread contour to the laser displacement sensor.

[0012] Optionally, the S5 comprises: a wheel tread three-dimensional point cloud graph, the X axis is the tread transverse coordinate, the Y axis is the wheel circumference direction, that is, the sampling interval of the encoder, and the Z axis direction is the distance from the tread contour to the laser displacement sensor.

[0013] Optionally, the S5 comprises: a wheel tread three-dimensional point cloud graph, the X axis is the tread transverse coordinate, the Y axis is the wheel circumference direction, that is, the sampling interval of the encoder, and the Z axis direction is the distance from the tread contour to the laser displacement sensor.

[0014] The wheel tread polygon detection system comprises a laser displacement sensor unit, a data processing unit, and a wheel tread three-dimensional point cloud graph.

[0015] The wheel tread polygon detection system comprises a laser displacement sensor unit, a data processing unit, and a wheel tread three-dimensional point cloud graph.

[0016] The data processing unit of the wheel tread polygon detection system comprises an upper computer and a first Bluetooth, the upper computer is connected with the first Bluetooth, after the data processing unit generates a wheel tread three-dimensional point cloud image, a plurality of wheel contour curves are extracted based on the wheel diameter direction, the wheel size is calculated, the wheel tread three-dimensional point cloud image is flattened, the wheel tread three-dimensional point cloud image and the wheel tread polygon data are distinguished, a wheel tread defect area is generated through difference detection, the data points gathered together are connected and numbered based on an image edge point clustering block algorithm, the damage defects of the wheel tread are obtained, and the depth, area and position of the damage defects are calculated.

[0017] The primary improvement of the application is to provide a wheel tread polygon detection method, the rotating wheel tread radial runout data is obtained in real time through a laser displacement sensor, an encoder, a single-chip microcomputer and a second Bluetooth, the mapping relationship between the wheel tread polygon data and the wheel tread surface point cloud data is constructed, and then the wheel tread size is accurately extracted and the defect area is accurately calculated through the difference between the wheel tread three-dimensional point cloud image and the wheel tread polygon data. The detection method can realize the wheel tread polygon detection without disassembling the wheel, and the detection method is accurate, convenient and fast, solves the problems of inconvenient detection and low reliability of the detection result of the existing wheel tread polygon detection method, and achieves the effect of conveniently and accurately detecting the wheel tread polygon. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 A simplified flowchart of the wheel tread polygon detection method of the application is shown in the figure.

[0019] Figure 2 A schematic diagram of the wheel tread polygon detection system of the application is shown in the figure.

[0020] Figure 3 A wheel circumference coordinate and a wheel polar coordinate example diagram of the application are shown in the figure.

[0021] In the figure, 1 is a data processing unit, 2 is a laser displacement sensor unit, 3 is an upper computer, 4 is a first Bluetooth, 5 is a single-chip microcomputer, 6 is a laser displacement sensor, 7 is an encoder, 8 is a permanent magnet supporting part, 9 is a steel rail, 10 is a wheel set, 11 is a second Bluetooth. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical scheme and advantages of the embodiments of the application more clear, the application will be further described in detail below with reference to the drawings and specific embodiments.

[0023] As shown in Figure 1 , Figure 2 , a wheel tread polygon detection method comprises the following steps.

[0024] Sl: Collect polygonal data of wheel tread.

[0025] Further, the Sl includes: the encoder 7 is close to the wheel tread of the wheel 10, and the encoder 7 rotates regularly when the wheel 10 rotates; the laser displacement sensor 6 receives the pulse signal transmitted by the encoder 7, and a group of data values correspond to one pulse signal; and the collected data is the distance from the laser displacement sensor 6 to the wheel tread of the wheel 10.

[0026] S2: Extract wheel surface point cloud data corresponding to the wheel tread radial runout data.

[0027] Further, the S2 includes: the data obtained by the laser displacement sensor 6 is transmitted to the single-chip microcomputer 5, and then the data is transmitted to the second Bluetooth 11 in a wireless manner through the first Bluetooth 4, so as to construct a mapping relationship between the wheel tread polygonal data and the wheel surface point cloud data, and the wheel surface point cloud data is extracted by the upper computer 3 through the second Bluetooth 11.

[0028] S3: In a rectangular coordinate system, extract Z data of a circular section at a position 70mm away from an inner side surface of the wheel in an X direction, as a nominal rolling circle of the wheel tread.

[0029] Further, the S3 includes: the wheel surface point cloud data extracted by the upper computer 3, and the nominal rolling circle of the wheel tread is extracted.

[0030] S4: Extract a wheel tread image.

[0031] Further, the S4 includes: on the basis of the nominal rolling circle of the wheel tread, a reference value of an average value of all rotation data is obtained, and a subsequent scanning line is used as a difference value of the reference value as a runout value of surface roughness, so as to extract the wheel tread image.

[0032] S5: Based on the wheel tread image and the nominal rolling circle of the wheel tread, generate a wheel tread three-dimensional point cloud image, a wheel tread circumferential coordinate image and a wheel tread polar coordinate image.

[0033] Further, the S5 includes: a Mat image structure is used, and the collected data is assigned to the image, so as to form a wheel tread three-dimensional data, an X axis of which is a lateral coordinate of the tread, a Y axis of which is a wheel circumference direction, i.e. a sampling interval of the encoder 7, and a Z axis direction is a distance from the tread profile to the laser displacement sensor 6, and then a wheel three-dimensional point cloud image, a wheel tread circumferential coordinate image and a wheel tread polar coordinate image are generated.

[0034] S6: Based on the wheel tread circumferential coordinate image and the wheel tread polar coordinate image, flatten the wheel tread three-dimensional point cloud image, and generate a wheel tread defect area.

[0035] Further, as Figure 3As shown in the wheel tread circumferential coordinate diagram and the wheel tread polar coordinate diagram, generating the wheel size comprises: after generating the wheel tread three-dimensional point cloud diagram, extracting a plurality of wheel tread contour curves based on the wheel diameter direction of the wheel, and calculating the wheel size.

[0036] Further, generating the defect area comprises: after generating the wheel tread three-dimensional point cloud diagram, flattening the wheel tread three-dimensional point cloud diagram, performing difference discrimination on the wheel tread three-dimensional point cloud diagram and the wheel tread polygon data, and generating the wheel defect area through difference detection.

[0037] Further, the difference detection is based on an image edge point clustering block algorithm, connected numbering of data points gathered together, obtaining the damage defect of the wheel tread, and calculating the depth, area and position.

[0038] Since the existing wheel tread polygon detection method has the problems of inconvenient detection and low reliability of detection results, the wheel tread polygon detection method provided by the present application acquires the rotating wheel tread polygon data through a laser displacement sensor, an encoder, a single-chip microcomputer and a second Bluetooth, constructs the mapping relationship between the wheel tread polygon data and the wheel tread point cloud data, and then realizes accurate extraction of the wheel size and accurate calculation of the defect area through difference discrimination of the wheel tread three-dimensional point cloud diagram and the wheel tread polygon data.

[0039] Correspondingly, as shown in the wheel tread polygon detection system, Figure 2 The present application provides a wheel tread polygon detection system, which comprises a laser displacement sensor unit 2 for collecting the tread radial runout data of the train wheel set, and a data processing unit 1 for constructing the mapping relationship between the wheel tread polygon data and the wheel tread point cloud data, and then realizing accurate extraction of the wheel tread size and accurate calculation of the defect area through difference discrimination of the wheel tread three-dimensional point cloud diagram and the wheel tread polygon data.

[0040] Further, the laser displacement sensor unit 2, the laser displacement sensor 6, the encoder 7, the single-chip microcomputer 5 and the second Bluetooth 11 are fixed on the permanent magnetic relying part 8, the permanent magnetic relying part 8 is adsorbed on the steel rail 9, the encoder 7 is closely attached to the tread of the wheel set 10 during collection, the encoder 7 rotates regularly when the wheel set 10 rotates, the laser displacement sensor 6 is connected with the encoder 7 and receives the pulse signal transmitted by the encoder 7, a data value corresponding to a pulse signal is collected, the laser displacement sensor 6 is connected with the single-chip microcomputer 5, the collected data is transmitted to the single-chip microcomputer 5, the single-chip microcomputer 5 is connected with the second Bluetooth 11, and then the second Bluetooth 11 communicates with the upper computer.

[0041] Further, the data processing unit 1, the upper computer 3 and the first Bluetooth 4 are connected, the first Bluetooth 4 receives the data transmitted by the second Bluetooth 11 in a wireless mode, and then the data is transmitted to the upper computer 3 for data processing.

[0042] The wheel set tread polygon detection method and system provided by the embodiment of the application are described in detail. For the device disclosed by the embodiment, since it corresponds to the method disclosed by the embodiment, the description is relatively simple, and the relevant part is described in the method part. It should be pointed out that the embodiment is only for illustrating the technical concept and characteristics of the application, the purpose is to enable those skilled in the art to understand the content of the application and implement it, and it cannot limit the protection scope of the application, and any equivalent changes or modifications made according to the spirit and essence of the application should be covered within the protection scope of the application.

Claims

1. A method for detecting polygonal shapes on wheelset treads, characterized in that, include: S1: Collect radial runout data of train wheelset tread; S2: Extract the point cloud data of the wheel tread surface corresponding to the radial runout data of the wheel tread; S3: In the rectangular coordinate system, extract the Z data of the circular cross section 70mm away from the inner end face of the wheel in the X direction, which is the nominal rolling circle of the wheelset tread; S4: Extract the wheel tread image based on the nominal rolling circle of the wheel tread; S5: Based on the wheel tread image and the nominal rolling circle of the wheel tread, generate a three-dimensional point cloud map of the wheel tread, a circumferential coordinate map of the wheel tread, and a polar coordinate map of the wheel tread. S6: Based on the circumferential coordinate map and polar coordinate map of the wheelset tread, flatten the three-dimensional point cloud map of the wheelset tread and generate the defect area of ​​the wheelset tread.

2. The method for detecting polygonal surfaces of wheelset treads according to claim 1, characterized in that, S1 includes: Data is collected in real time by scanning the rotating wheelset using a laser displacement sensor, encoder, microcontroller, and a second Bluetooth connection.

3. The method for detecting polygonal surfaces of wheelset treads according to claim 1, characterized in that, S2 includes: Obtain the radial runout data of the rotating wheelset tread, which is the distance from the laser displacement sensor to the wheelset tread. Construct a mapping relationship between the polygonal data of the wheelset tread and the point cloud data of the wheelset surface.

4. The method for detecting polygonal surfaces of wheelset treads according to claim 1, characterized in that, S5 includes: The three-dimensional point cloud map of the wheel tread has the X-axis as the lateral coordinate of the tread, the Y-axis as the wheel circumference (i.e., the encoder sampling interval), and the Z-axis as the distance from the tread profile to the laser displacement sensor.

5. The method for detecting polygonal surfaces of wheelset treads according to claim 1, characterized in that, Generate wheelset dimensions, including: After generating the three-dimensional point cloud map of the wheelset tread, multiple wheelset tread profile curves are extracted based on the wheelset diameter direction, and the wheelset dimensions are calculated.

6. The method for detecting polygonal surfaces of wheelset treads according to claim 3, characterized in that, The generated defect areas include: After generating the three-dimensional point cloud map of the wheelset tread, the three-dimensional point cloud map of the wheelset tread is flattened, and the difference between the three-dimensional point cloud map of the wheelset tread and the polygonal data of the wheelset tread is judged. The defect area of ​​the wheelset tread is generated by the difference detection.

7. The method for detecting polygonal surfaces of wheelset treads according to claim 6, characterized in that, The difference detection is based on an image edge point clustering and block division algorithm. It connects and numbers the data points that are clustered together to obtain the damage defects on the wheel tread and calculates their depth, area and location.

8. A wheelset tread polygon detection system for implementing the method of claim 1, characterized in that, include: A laser displacement sensor unit is used to collect polygonal data of the train wheelset tread surface; The data processing unit constructs a mapping relationship between the wheelset tread polygon data and the wheelset tread point cloud data. Then, by judging the differences between the three-dimensional point cloud map of the wheelset tread and the polygon data of the wheelset tread, it realizes the extraction of wheelset dimensions and the calculation of defect areas.

9. A wheelset tread polygon detection system according to claim 8, characterized in that, The laser displacement sensor (6), encoder (7), microcontroller (5), and second Bluetooth (11) of the laser displacement sensor unit (2) are all fixed on the permanent magnet support (8). The permanent magnet support (8) is attached to the rail (9). During data acquisition, the encoder (7) is in close contact with the tread surface of the wheel set (10). When the wheel set (10) rotates, the encoder (7) rotates in a regular manner. The laser displacement sensor (6) is connected to the encoder (7) and receives the pulse signal transmitted by the encoder (7). One pulse signal corresponds to one data value for acquisition. The laser displacement sensor (6) is connected to the microcontroller (5). The acquired data is transmitted to the microcontroller (5). The microcontroller (5) is connected to the second Bluetooth (11) and then communicates with the host computer through the second Bluetooth (11).

10. A wheelset tread polygon detection system according to claim 8, characterized in that, The host computer (3) of the data processing unit (1) is connected to the first Bluetooth (4). The first Bluetooth (4) receives data transmitted from the second Bluetooth (11) wirelessly and then transmits it to the host computer (3) for data processing.

11. A wheelset tread polygon detection system according to claim 9, characterized in that, The laser displacement sensor (6) is a line laser displacement sensor.

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