Wheel axle positioning method and inspection robot

Abstract

The invention discloses a wheel axis fixing method and a railway inspection robot, and the method comprises the steps: obtaining the collection data of the inspection robot for each wheel, the collection data comprising a first distance, a first angle and a robot inclination angle at each moment; aiming at the collected data of each wheel, correcting the first distance and the first angle corresponding to the same moment based on the inclination angle of the robot, and respectively obtaining a second distance and a second angle; obtaining a to-be-selected moment when the second distance of each wheel meets a preset distance range, and calculating a relative angle difference between second angles corresponding to every two to-be-selected moments; according to the positions of the inspection robot corresponding to the two to-be-selected moments with the minimum relative angle difference, the center position of the wheel is determined, accurate positioning of the wheel can be completed by means of the collected data of the inspection robot for each wheel, and the real-time performance is high.

Description

Technical Field

[0001] This invention relates to the field of railway freight car inspection technology, and in particular to a wheel axle fixing method and an inspection robot. Background Technology

[0002] Railway freight car inspection robots utilize AGVs (Automated Guided Vehicles) or RGVs (Rail Guided Vehicles) to scan and photograph railway freight cars, and then employ automatic recognition methods for image identification. During the robot inspection process, the acquired images need to be segmented and positioned by car and bogie; therefore, high-precision axle positioning is a key technical problem that needs to be solved.

[0003] In RGV robot systems, laser-based axis positioning technology is typically used, which involves using laser rangefinders to detect the wheels in real time. Figure 1 As shown, the dashed line represents the effective area for detecting the wheel using a laser rangefinder. The relative position of the RGV track and the railway freight car track is fixed, and the distance between the laser rangefinder sensor and the wheel is a fixed value L. Therefore, when the rangefinder sensor detects the effective area of ​​the wheel, the returned distance value is always near L; however, when the rangefinder sensor does not detect the wheel, the returned distance deviates significantly from L. The railway freight car wheel has a standard symmetrical structure. By analyzing the measured distance value fed back by the laser sensor, the center of the wheel can be accurately located. Currently, using this method, when the RGV's operating speed is no more than 10 km / h, the axis-fixing accuracy can reach the millimeter level, meeting the requirements for image segmentation and positioning.

[0004] For each wheel, filter out the values ​​with a distance of L from the returned distance values, where X i-1 The coordinate point is the position of RGV at the moment when the distance sensor first returns a value of L, X i The coordinate point is the position of the RGV at time L, when the distance sensor last returned a value. Therefore, the coordinates of the wheel center are X. i-1 +(X) i -X i-1 This method is simple, reliable, and logically clear, and is widely used in RGV robot systems.

[0005] However, using this axis-fixing method in AGV robot systems results in a sharp drop in axis-fixing accuracy, reaching levels of several centimeters or even tens of centimeters. The fundamental reason is that AGVs lack physical tracks and exhibit a noticeable serpentine motion during movement. Furthermore, when encountering obstacles, they must avoid them, further increasing the deviation of this axis-fixing method. Figure 2 As shown.

[0006] 1) The RGV has a fixed travel trajectory, and its laser rangefinder is always perpendicular to the wheel. The distance measurement return value has a constant range of L, making positioning relatively easy. In contrast, the AGV has a more obvious serpentine movement and needs to detour when encountering obstacles. The position of the AGV body and the position of the railway freight car are uncertain, and it is impossible to use fixed parameters to determine the positioning of the wheel.

[0007] 2) When the AGV body and the railway freight car body are at a random angle, the laser rangefinder can detect the wheel tread (see figure below). The wheel tread is very smooth due to wheel-rail friction. The laser rangefinder cannot give an accurate distance value when detecting a smooth and reflective surface, and it is easy to produce a lot of erroneous data.

[0008] Low axis-fixed accuracy poses a significant challenge to accurate image segmentation and localization. Current conventional approaches address this issue as follows: First, initial image segmentation and localization are performed using axis-fixed data. Then, image recognition methods are applied to perform secondary identification of key features in the image, and based on these identified features, the image is segmented and localized again for precise accuracy. This method typically requires the recognition algorithm to be deployed locally on the robot, and the algorithm suffers from a high rate of false recognitions, resulting in low system robustness and impacting overall system reliability. Summary of the Invention

[0009] The purpose of this invention is to provide at least one wheel axle fixing method and an inspection robot, which can at least solve the technical problem of low axle fixing accuracy of railway inspection robots in the prior art.

[0010] To address the aforementioned technical problems, at least one embodiment of this application provides a wheel axle fixing method, comprising: The inspection robot collects data for each wheel. The collected data includes a first distance, a first angle, and a robot tilt angle at each moment. The first distance is the vertical distance between the wheel's measured point and the reference surface. The first angle is the angle between the wheel's measured point and the straight line where the inspection robot is located and the reference surface. The reference surface is the plane perpendicular to the direction of the inspection robot's movement. For the collected data of each wheel, based on the robot tilt angle, the first distance and the first angle corresponding to the same moment are corrected to obtain the second distance and the second angle respectively. The second distance is the vertical distance of the wheel test point relative to the preset ideal surface, and the second angle is the angle between the wheel test point and the straight line where the inspection robot is located and the preset ideal surface. The preset ideal surface is a plane parallel to the side of the wheel, and the robot tilt angle is the angle between the reference surface and the preset ideal surface. Obtain the candidate time when the second distance of each wheel satisfies the preset distance range, and calculate the relative angle difference of the second angle corresponding to every two candidate times; The center position of the wheel is determined based on the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

[0011] At least one embodiment of this application also provides a wheel axle fixing device, comprising: The acquisition module is used to acquire the data collected by the inspection robot for each wheel. The data includes a first distance, a first angle and a robot tilt angle at each moment. The first distance is the vertical distance of the wheel measurement point relative to the reference surface. The first angle is the angle between the wheel measurement point and the straight line where the inspection robot is located and the reference surface. The reference surface is the vertical plane of the inspection robot's forward direction. The correction module is used to correct the first distance and first angle corresponding to the same moment for each wheel based on the robot tilt angle, and obtain a second distance and a second angle respectively. The second distance is the vertical distance of the wheel test point relative to the preset ideal surface, and the second angle is the angle between the wheel test point and the straight line where the inspection robot is located and the preset ideal surface. The preset ideal surface is a plane parallel to the side of the wheel, and the robot tilt angle is the angle between the reference surface and the preset ideal surface. The calculation module is used to obtain the candidate time when the second distance of each wheel satisfies the preset distance range, and to calculate the relative angle difference of the second angle corresponding to each two candidate times; The axis-fixing module is used to determine the center position of the wheel based on the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

[0012] At least one embodiment of this application also provides an inspection robot, including a guided vehicle body, and a reflective photoelectric sensor, a laser profilometer, a tilt sensor and a trigger plate mounted on the guided vehicle body; The reflective photoelectric sensor is installed on the side of the guided vehicle near the wheels and is used for coarse positioning of the wheels. The trigger plate is used to activate when the reflective photoelectric sensor detects a wheel, and simultaneously trigger the laser profiler and tilt sensor; The laser profilometer is installed on the side of the guide vehicle near the wheels and is used to collect distance data of the guide vehicle body relative to the vehicle. The tilt sensor is used to collect the tilt angle of the guide vehicle body relative to an ideal surface, which is a plane parallel to the vertical direction of the wheel position.

[0013] At least one embodiment of this application also provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the wheel axle fixing method described above.

[0014] At least one embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described wheel axle fixing method.

[0015] The wheel axle positioning method, apparatus, electronic device, and computer-readable storage medium provided in the embodiments of this application obtain a second distance and a second angle based on a preset ideal plane by correcting a first distance and a first angle based on a reference plane where the inspection robot is located. The center position of the wheel is determined by the position of the inspection robot corresponding to the two second angles when the relative angle difference between the two second angles corresponding to the same wheel is the smallest. This method has low requirements for robot computing performance, and the wheel can be accurately positioned after the hardware sensors collect the data. It has high real-time performance, facilitates the rapid identification of problems in the axle positioning process based on the collected data output by the sensors, and has good system maintainability.

[0016] In some optional embodiments, the expression for the second distance is: Dcp=sin(Ap+Q) Dp / sin(Ap) Where Dcp is the second distance, Ap is the first angle, Dp is the first distance, and Q is the robot tilt angle.

[0017] In some optional embodiments, the expression for the second angle is: Acp = Ap Q Where Acp is the second angle, Ap is the first angle, and Q is the robot tilt angle; When the wheel being measured is located in the forward direction of the inspection robot, then Acp = Ap Q; When the measured point of the vehicle is located in the backward direction of the inspection robot's position, then Acp = Ap Q.

[0018] In some optional embodiments, the step of determining the center position of the wheel based on the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference includes: The center position of the wheel is determined to be the midpoint between the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

[0019] In some optional embodiments, the expression for the center position of the wheel is: X c X i-1 +(X) i -X i-1 ) / 2 Among them, X c X is the coordinate point of the center position of the wheel; i-1 Let X be the coordinates of the inspection robot corresponding to one of the candidate times; i Let be the coordinates of the inspection robot corresponding to another candidate time.

[0020] In some optional embodiments, the method further includes: Acquire wheel positioning data, which includes the time when the wheel was identified and the wheel's position information at each time. For each wheel, from the moment it is first detected to the moment it is last detected, the inspection robot is driven to collect data from each wheel at a preset sampling frequency. Attached Figure Description

[0021] One or more embodiments are illustrated by way of example with reference to the accompanying drawings, and these illustrative descriptions do not constitute a limitation on the embodiments.

[0022] Figure 1 This is a schematic diagram illustrating the effective area for laser rangefinders to detect vehicles in existing technologies. Figure 2 This is a schematic diagram of the operating trajectories of RGVs and AGVs in existing technologies; Figure 3 A schematic flowchart of a wheel axle fixing method provided in one embodiment of this application; Figure 4 A schematic diagram of a second distance data curve generated along the forward direction of the inspection robot, provided for another embodiment of this application; Figure 5 A schematic diagram showing the distance and angle between the measured point of the wheel and the reference and ideal surfaces, provided for another embodiment of this application; Figure 6 A schematic diagram of a wheel and inspection robot provided for another embodiment of this application; Figure 7 A schematic diagram of a wheel and an inspection robot from another perspective, provided for another embodiment of this application; Figure 8A schematic diagram of a wheel axle fixing device provided for another embodiment of this application; Figure 9 A schematic diagram of the structure of an electronic device provided for another embodiment of this application.

[0023] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the various embodiments of this application will be described in detail below with reference to the accompanying drawings. However, those skilled in the art will understand that many technical details have been provided in the various embodiments of this application to help readers better understand this application. However, the technical solutions claimed in this application can be implemented even without these technical details and various changes and modifications based on the following embodiments. The division of the various embodiments below is for the convenience of description and should not constitute any limitation on the specific implementation of this application. The various embodiments can be combined with and referenced by each other without contradiction.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0027] To address the technical problem of low axle positioning accuracy in existing railway inspection robots, this invention proposes a wheel axle positioning method. The implementation details of the wheel axle positioning method in this embodiment are described below. The following content is only for ease of understanding and is not necessary for implementing this solution.

[0028] Example 1 Figure 3 This is a schematic flowchart illustrating a wheel axle fixing method provided in an embodiment of this disclosure. Figure 3 As shown, a wheel axle fixing method includes: Step 110: Obtain the data collected by the inspection robot for each wheel. The collected data includes the first distance, the first angle, and the robot tilt angle at each moment. The first distance is the vertical distance between the wheel test point and the reference surface. The first angle is the angle between the wheel test point and the straight line where the inspection robot is located and the reference surface. The reference surface is the vertical plane of the inspection robot's forward direction.

[0029] Specifically, the inspection robot is used to photograph and identify railway freight cars. In this embodiment, the inspection robot is illustrated using an AGV as an example. The AGV is equipped with a data acquisition module for collecting data from the wheels. The collected data includes a first distance, a first angle, and the robot tilt angle at various times. The first distance is the vertical distance between the wheel measurement point and the reference surface. The first angle is the angle between the wheel measurement point, the straight line where the inspection robot is located, and the reference surface. The reference surface is the plane perpendicular to the direction of travel of the inspection robot.

[0030] In one example, the AGV is equipped with a laser profilometer to collect distance data within its field of view, and an angle sensor to identify the robot's posture, collect angle information, and compensate for the angle of the laser profilometer data.

[0031] In one example, to ensure the synchronization of data acquired by the laser profiler and the tilt sensor, the AGV is also equipped with a synchronization trigger board. The synchronization trigger board is used to synchronize the laser profiler and the tilt sensor, ensuring that the laser profiler and the tilt sensor acquire data at the same time.

[0032] In one example, the reference plane is always perpendicular to the direction of travel of the inspection robot, including situations where the inspection robot needs to avoid obstacles and detour when it encounters them during its movement.

[0033] Step 120: For the collected data of each wheel, based on the robot tilt angle, the first distance and the first angle corresponding to the same moment are corrected to obtain the second distance and the second angle respectively. The second distance is the vertical distance of the wheel test point relative to the preset ideal surface, and the second angle is the angle between the wheel test point and the straight line where the inspection robot is located and the preset ideal surface. The preset ideal surface is a plane parallel to the side of the wheel, and the robot tilt angle is the angle between the reference surface and the preset ideal surface.

[0034] Specifically, because the AGV has no physical track, it exhibits a noticeable serpentine movement during its travel. Furthermore, it needs to avoid obstacles when encountering them. Therefore, the reference plane perpendicular to the AGV's forward direction is not necessarily parallel to the wheel surface. To achieve high-precision wheel alignment, the first distance and first angle corresponding to the same moment need to be corrected based on the robot's tilt angle to obtain a second distance and a second angle. The second distance is the vertical distance of the wheel's measured point relative to a preset ideal plane, and the second angle is the angle between the wheel's measured point, the line where the inspection robot is located, and the preset ideal plane. The preset ideal plane is a plane parallel to the wheel's side surface, and the robot's tilt angle is the angle between the reference plane and the preset ideal plane. Here, the wheel's side surface refers to a plane perpendicular to the vehicle's travel direction.

[0035] Furthermore, if the preset ideal surface is a plane parallel to the side of the wheel, then the robot tilt angle is the angle between the reference surface and the preset ideal surface. By converting the vertical distance of the wheel test point relative to the reference surface into the vertical distance of the wheel test point relative to the preset ideal surface, the second distance is obtained. And by converting the angle between the line connecting the wheel test point and the inspection robot and the reference surface into the angle between the line connecting the wheel test point and the inspection robot and the preset ideal surface, the second angle is obtained.

[0036] In one example, for ease of calculation, the ideal surface is assumed to be a plane that passes through the location of the inspection robot and is parallel to the side of the wheel.

[0037] Step 130: Obtain the candidate time when the second distance of each wheel satisfies the preset distance range, and calculate the relative angle difference of the second angle corresponding to each two candidate times.

[0038] Specifically, there are two equidistant regions on the wheel surface relative to the ideal surface. From all the correction data, the direction angle corresponding to the equidistant region is selected. Based on the relative angle difference between the two second angles corresponding to the second distance of the same wheel, the center position of the wheel can be determined, thus achieving the wheel's fixed axis.

[0039] Step 140: Determine the center position of the wheel based on the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

[0040] Specifically, such as Figure 4 As shown, for each wheel, the acquired data from the inspection robot includes a distance curve generated along the robot's forward direction, where L is the second curve at each time point, and X is the position coordinate of the inspection robot at each time point, where X... i and Xi-1 The coordinates of the inspection robot's location at the candidate time when the second distance to the same wheel meets a preset distance range are determined. The center position of the wheel is determined based on the inspection robot's location at the two candidate times with the smallest relative angle difference.

[0041] In this embodiment, by correcting the first distance and first angle obtained based on the reference surface, a second distance and second angle based on the preset ideal surface are obtained. The center position of the wheel is determined according to the position of the inspection robot at the selected time when the second distance of the same wheel meets the preset distance range. This method has low requirements for the robot's computing performance. The wheel can be accurately positioned after the hardware sensor collects the data, which has high real-time performance. It is also convenient to quickly identify problems in the axis setting process based on the collected data output by the sensor, and the system has good maintainability.

[0042] In some embodiments, the expression for the second distance is: Dcp=sin(Ap+Q) Dp / sin(Ap) Where Dcp is the second distance, Ap is the first angle, Dp is the first distance, and Q is the robot tilt angle.

[0043] Specifically, such as Figure 5 As shown, point P is the wheel being measured, point O is the reference point (i.e., the location of the inspection robot), and Q is the vehicle tilt angle. The first distance Dp is the vertical distance of point P relative to the reference surface; the first angle Ap is the angle between the line connecting the wheel being measured point P and the inspection robot O and the reference surface; based on point P, the first distance is corrected to obtain the distance of point P relative to the ideal surface, i.e., the second distance Dcp.

[0044] In some embodiments, the expression for the second angle is: Acp = Ap Q Where Acp is the second angle, Ap is the first angle, and Q is the robot tilt angle; When the wheel being measured is located in the forward direction of the inspection robot, then Acp = Ap Q; When the measured point of the vehicle is located in the backward direction of the inspection robot's position, then Acp = Ap Q.

[0045] Specifically, such as Figure 5As shown, point P is the wheel being measured, point O is the reference point (i.e., the location of the inspection robot), and Q is the vehicle tilt angle. The first distance Dp is the vertical distance of point P relative to the reference surface; the first angle Ap is the angle between the line connecting the wheel being measured point P and the inspection robot O and the reference surface; based on point P, the first angle is corrected to obtain the angle between the line connecting the wheel being measured point P and the inspection robot O and the preset ideal surface, which is the second angle Acp.

[0046] Furthermore, the expression for the second angle Acp is: Acp = Ap Q When point P is to the left of the reference point, a plus sign is used; otherwise, a minus sign is used.

[0047] In some embodiments, the step of determining the center position of the wheel based on the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference includes: The center position of the wheel is determined to be the midpoint between the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

[0048] In some embodiments, the expression for the center position of the wheel is: X c X i-1 +(X) i -X i-1 ) / 2 Among them, X c X is the coordinate point of the center position of the wheel; i-1 Let X be the coordinates of the inspection robot corresponding to one of the candidate times; i Let be the coordinates of the inspection robot corresponding to another candidate time.

[0049] Specifically, such as Figure 4 As shown, for each wheel, the acquired data from the inspection robot includes a distance curve generated along the robot's forward direction, where L is the second curve at each time point, and X is the position coordinate of the inspection robot at each time point, where X... i and X i-1 The coordinates of the inspection robot's location at the selected moment when the second distance of the same wheel meets the preset distance range can be used to determine the center position of the wheel based on the locations of the inspection robots corresponding to the two second angles when the relative angle difference is the smallest.

[0050] In some embodiments, the method further includes: Acquire wheel positioning data, which includes the time when the wheel was identified and the wheel's position information at each time. For each wheel, from the moment it is first detected to the moment it is last detected, the inspection robot is driven to collect data from each wheel at a preset sampling frequency.

[0051] Specifically, when the inspection robot starts working, it first acquires the positioning data of the wheels, which includes the time when the wheels are identified and the position information of the wheels at each time. In one example, a reflective photoelectric sensor is used to collect positioning data. When the reflective photoelectric sensor detects a wheel obstruction, it obtains the time when the wheel was identified and the wheel's position information at each time. Specifically, for each wheel, the inspection robot collects data from the moment it first identifies the wheel to the moment it last identifies it, at a preset sampling frequency.

[0052] In one example, the inspection robot is also equipped with a synchronization trigger board. When the reflective photoelectric sensor detects wheel obstruction, the synchronization trigger board is activated. The synchronization trigger board is used to synchronously trigger the acquisition device to collect the first distance data and the first angle data.

[0053] In one example, the synchronous trigger board triggers the acquisition device to sample at a preset fixed frequency. Each time the synchronous trigger board is triggered, it acquires a set of first distance data, the first angle data corresponding to the first distance data, and the robot tilt angle at that moment.

[0054] Furthermore, the preset fixed frequency is set to 100Hz. Assuming the inspection robot's walking speed is 1m / s, a set of data is sampled every 10mm. The maximum positioning error of the wheel center is 10mm. If it is necessary to further reduce the error, the triggering frequency of the synchronous trigger board can be increased.

[0055] The wheel axle positioning method provided in this embodiment corrects the first distance and first angle obtained based on a reference surface to obtain a second distance and second angle based on a preset ideal surface. The center position of the wheel is determined according to the position of the inspection robot at the selected time when the second distance of the same wheel meets the preset distance range. This method has low requirements for robot computing performance. The wheel can be accurately positioned after the hardware sensor collects the data, which has high real-time performance. It is also convenient to quickly identify problems in the axle positioning process based on the collected data output by the sensor, and the system has good maintainability.

[0056] Example 2 Another embodiment of this application relates to a high-precision axis determination method for a railway freight car inspection robot. The railway freight car inspection robot is an automatically navigated trackless guided vehicle, such as an AGV. The railway freight car inspection robot is equipped with a reflective photoelectric sensor, a laser profilometer, a tilt sensor, a trigger plate, and a computing module. The computing module is a module with the ability to calculate data from the reflective photoelectric sensor, the laser profilometer, and the tilt sensor. It can be a computing unit in the robot's industrial control computer or a separate computing unit.

[0057] The reflective photoelectric sensor, laser profilometer, tilt sensor, trigger plate, and computing module are all installation devices on the robot body. The reflective photoelectric sensor is used for coarse positioning of the wheels, and the synchronous trigger plate is activated when wheel occlusion is detected. The laser profilometer is used to collect distance data within the field of view and feed back distance information. The tilt sensor is used to identify the robot body's posture, feed back angle information, and perform angle compensation on the profilometer data. The trigger plate is used for synchronous triggering of the laser profilometer and tilt sensor to ensure that the data fed back by the two sensors are collected by the robot at the same time. The computing module is used to collect and analyze the data from the laser profilometer and tilt sensor.

[0058] Furthermore, one tilt sensor is used, fixedly connected to the AGV body, and can output the tilt angle of the AGV relative to the reference plane; one reflective photoelectric sensor is used, located on the surface of the vehicle body, 200mm from the top surface of the rail in the vertical direction; one laser profilometer is used, located on the surface of the vehicle body, 150mm from the top surface of the rail in the vertical direction. The reflective photoelectric sensor and the laser profilometer are aligned vertically and do not interfere with each other structurally.

[0059] The high-precision axis-fixing method for the railway freight car inspection robot includes the following steps: 1) The system starts up and the reflective photoelectric sensor begins to work.

[0060] 2) When the optical path of the reflective photoelectric sensor is blocked by the wheel, the synchronous trigger board starts to work.

[0061] 3) The synchronous trigger board triggers the profilometer and tilt sensor to sample at a fixed frequency (e.g., 100Hz). Each time the trigger board is triggered, the system's calculation unit obtains a set of distance data Di, the corresponding direction angle Ai, and the vehicle tilt angle Qi at that moment. Distance data Di is the distance between the wheel and the tilt surface measured at the vehicle tilt angle Qi. Direction angle Ai is the angle between the measured point and the reference point. For example... Figure 5 As shown, with reference point O, vehicle tilt angle Q, and measured point P, the laser profilometer returns the vertical distance Dp of point P relative to the reference surface and the angle Ap of point P relative to reference point O.

[0062] 4) Using the tilt angle Qi, correct the acquired distance array Di and angle array Ai to obtain the distance data Dci and direction angle array Aci relative to the ideal reference plane. The ideal plane refers to a plane parallel to the wheel surface. For example... Figure 5 As shown, point P is corrected to obtain the distance Dcp = sin(Ap + Q) * Dp / sin(Ap) relative to the ideal surface, and the direction angle Acp of point P relative to the ideal surface is Ap + (-)Q. A plus sign is used when point P is to the left of the reference point, and a minus sign is used otherwise. The correction principle is the same for other measured points.

[0063] 5) In an ideal scenario, the corrected data shows two equidistant regions on the wheel surface relative to the ideal surface. From all the corrected data, the direction angles corresponding to these equidistant regions are selected. The position of the AGV body corresponding to the smallest difference in direction angles is the center of the wheel. Assuming the trigger frequency of the synchronous trigger plate is 100Hz and the AGV's traveling speed is 1m / s, then a set of data is sampled every 10mm. The maximum positioning error of the wheel center is 10mm. To further reduce the error, the trigger frequency of the synchronous trigger plate can be increased.

[0064] 6) When the optical path of the reflective photoelectric sensor is no longer blocked by the wheel, the synchronous trigger board stops working, the tilt sensor and laser profiler do not output signals, and the AGV continues to move forward until the next wheel triggers the reflective photoelectric sensor, and the fixed-axis process restarts. The advantage of this working mode is that the system does not need to acquire and process data at high frequency in real time, reducing system performance requirements and improving system stability.

[0065] The high-precision axle positioning method for railway freight car inspection robots provided in this embodiment uses hardware sensors to locate the wheels, which has low requirements for the robot's computing performance. After the hardware sensors collect data, they can complete the precise positioning of the wheels, resulting in high real-time performance. The hardware system has a simple principle and works according to specific logic, resulting in high overall system reliability. After a problem is detected, it is easy to quickly locate the problem based on the sensor output results, and the system has good maintainability.

[0066] Example 3 Another embodiment of this application relates to a railway freight car inspection robot, which includes: a guide car body, and a reflective photoelectric sensor, a laser profilometer, an tilt sensor, and a trigger plate installed on the guide car body; The reflective photoelectric sensor is installed on the side of the guided vehicle near the wheels and is used for coarse positioning of the wheels. The trigger plate is used to activate when the reflective photoelectric sensor detects a wheel, and simultaneously trigger the laser profiler and tilt sensor; The laser profilometer is installed on the side of the guide vehicle near the wheels and is used to collect distance data of the guide vehicle body relative to the vehicle. The tilt sensor is used to collect the tilt angle of the guide vehicle body relative to an ideal surface, which is a plane parallel to the vertical direction of the wheel position.

[0067] Specifically, such as Figure 6 and Figure 7 As shown, the railway freight car inspection robot includes a reflective photoelectric sensor, a laser profilometer, a tilt sensor, a trigger plate, and a computing module. The computing module is a module with the ability to calculate data from the reflective photoelectric sensor, the laser profilometer, and the tilt sensor. It can be a computing unit in the robot's industrial control computer or a separate computing unit.

[0068] The reflective photoelectric sensor, laser profilometer, tilt sensor, trigger plate, and computing module are all installation devices on the robot body. The reflective photoelectric sensor is used for coarse positioning of the wheels, and the synchronous trigger plate is activated when wheel occlusion is detected. The laser profilometer is used to collect distance data within the field of view and feed back distance information. The tilt sensor is used to identify the robot body's posture, feed back angle information, and perform angle compensation on the profilometer data. The trigger plate is used for synchronous triggering of the laser profilometer and tilt sensor to ensure that the data fed back by the two sensors are collected by the robot at the same time. The computing module is used to collect and analyze the data from the laser profilometer and tilt sensor.

[0069] The laser profilometer can acquire the profile of the cross section within the field of view, with the laser profilometer surface as the reference plane.

[0070] The structural layout of the railway freight car inspection robot is as follows: Figure 6 As shown: 1-AGV, 2-tilt sensor, 3-laser profilometer, 4-reflective photoelectric sensor, 5-synchronous trigger board, 6-computing module. The AGV is an autonomously guided, trackless steerable vehicle. There is one tilt sensor, fixedly connected to the AGV body, which outputs the tilt angle of the AGV relative to a reference plane. There is one reflective photoelectric sensor, located on the vehicle surface, 200mm vertically from the top surface of the rail. There is one laser profilometer, located on the vehicle surface, 150mm vertically from the top surface of the rail. The reflective photoelectric sensor and the laser profilometer are aligned vertically and do not interfere with each other structurally.

[0071] The steps for locating the wheel center of this railway freight car inspection robot are as follows: 1) The system starts up and the reflective photoelectric sensor begins to work.

[0072] 2) When the optical path of the reflective photoelectric sensor is blocked by the wheel, the synchronous trigger board starts to work.

[0073] 3) The synchronous trigger board triggers the profilometer and tilt sensor to sample at a fixed frequency (e.g., 100Hz). Each time the trigger board is triggered, the system's calculation unit obtains a set of distance data Di, the corresponding direction angle Ai, and the vehicle tilt angle Qi at that moment. Distance data Di is the distance between the wheel and the tilt surface measured at the vehicle tilt angle Qi. Direction angle Ai is the angle between the measured point and the reference point.

[0074] 4) Using the tilt angle Qi, correct the obtained distance array Di and angle array Ai to obtain the distance data Dci and direction angle array Aci relative to the ideal reference plane. The ideal plane refers to a plane parallel to the wheel surface. The distance Dcp of point P relative to the ideal plane is sin(Ap+Q). Dp / sin(Ap), where Acp is the direction angle of point P relative to the ideal plane, = Ap + (-)Q. A plus sign is used when point P is to the left of the reference point, and a minus sign is used otherwise. The correction principle is the same for other measured points.

[0075] 5) In an ideal scenario, the corrected data shows two equidistant regions on the wheel surface relative to the ideal surface. From all the corrected data, the direction angles corresponding to these equidistant regions are selected. The position of the AGV body corresponding to the smallest difference in direction angles is the center of the wheel. Assuming the trigger frequency of the synchronous trigger plate is 100Hz and the AGV's traveling speed is 1m / s, then a set of data is sampled every 10mm. The maximum positioning error of the wheel center is 10mm. To further reduce the error, the trigger frequency of the synchronous trigger plate can be increased.

[0076] 6) When the optical path of the reflective photoelectric sensor is no longer blocked by the wheel, the synchronous trigger board stops working, the tilt sensor and laser profiler do not output signals, and the AGV continues to move forward until the next wheel triggers the reflective photoelectric sensor, and the fixed-axis process restarts. The advantage of this working mode is that the system does not need to acquire and process data at high frequency in real time, reducing system performance requirements and improving system stability.

[0077] The railway freight car inspection robot provided in this embodiment uses hardware sensors to locate the wheels, which has low requirements for the robot's computing performance; the hardware sensors can complete the precise positioning of the wheels after collecting data, and the system has high real-time performance; the hardware system has a simple principle and works according to specific logic, so the overall reliability of the system is high; after a problem is found, it is easy to quickly locate the problem based on the sensor output results, and the system has good maintainability.

[0078] Example 4 Another embodiment of this application relates to a wheel axle fixing device. The implementation details of the wheel axle fixing device of this embodiment are described below. The following implementation details are provided for ease of understanding and are not essential for implementing this solution. A schematic diagram of the wheel axle fixing device of this embodiment can be seen as follows: Figure 8 As shown, it includes an acquisition module 801, a correction module 802, a calculation module 803, and a fixed-axis module 804.

[0079] The acquisition module 801 is used to acquire the data collected by the inspection robot for each wheel. The data includes a first distance, a first angle and a robot tilt angle at each moment. The first distance is the vertical distance between the wheel measurement point and the reference surface. The first angle is the angle between the wheel measurement point and the straight line where the inspection robot is located and the reference surface. The reference surface is the vertical plane of the inspection robot's forward direction. The correction module 802 is used to correct the first distance and first angle corresponding to the same moment for each wheel based on the robot tilt angle, and obtain a second distance and a second angle respectively. The second distance is the vertical distance of the wheel test point relative to the preset ideal surface, and the second angle is the angle between the wheel test point and the straight line where the inspection robot is located and the preset ideal surface. The preset ideal surface is a plane parallel to the side of the wheel, and the robot tilt angle is the angle between the reference surface and the preset ideal surface. The calculation module 803 is used to obtain the candidate time when the second distance of each wheel satisfies the preset distance range, and to calculate the relative angle difference of the second angle corresponding to each two candidate times; The fixed-axis module 804 is used to determine the center position of the wheel based on the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

[0080] In some optional embodiments, the expression for the second distance is: Dcp=sin(Ap+Q) Dp / sin(Ap) Where Dcp is the second distance, Ap is the first angle, Dp is the first distance, and Q is the robot tilt angle.

[0081] In some optional embodiments, the expression for the second angle is: Acp = Ap Q Where Acp is the second angle, Ap is the first angle, and Q is the robot tilt angle; When the wheel being measured is located in the forward direction of the inspection robot, then Acp = Ap Q; When the measured point of the vehicle is located in the backward direction of the inspection robot's position, then Acp = Ap Q.

[0082] In some optional embodiments, the axis-fixing module is further configured to determine the center position of the wheel as the midpoint between the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

[0083] In some optional embodiments, the expression for the center position of the wheel is: X c X i-1 +(X) i -X i-1 ) / 2 Among them, X c X is the coordinate point of the center position of the wheel; i-1 Let X be the coordinates of the inspection robot corresponding to one of the candidate times; i Let be the coordinates of the inspection robot corresponding to another candidate time.

[0084] In some optional embodiments, a positioning module is also included, which is used to acquire positioning data of the wheel, the positioning data including the time when the wheel was identified and the position information of the wheel at each time. For each wheel, from the moment it is first detected to the moment it is last detected, the inspection robot is driven to collect data from each wheel at a preset sampling frequency.

[0085] In this embodiment, by correcting the first distance and first angle obtained based on the reference surface, a second distance and second angle based on a preset ideal surface are obtained. The center position of the wheel is determined according to the position of the inspection robot at the selected time when the second distance of the same wheel meets the preset distance range. This method has low requirements for the robot's computing performance. The wheel can be accurately positioned after the hardware sensor collects the data, which has high real-time performance. It is also convenient to quickly identify problems in the axis setting process based on the collected data output by the sensor, and the system has good maintainability.

[0086] It is worth mentioning that all modules involved in this embodiment are logical modules. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. Furthermore, to highlight the innovative aspects of this application, this embodiment does not introduce units that are not closely related to solving the technical problems proposed in this application; however, this does not mean that other units are absent in this embodiment.

[0087] It should be noted that, in this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0088] Example 5 Another embodiment of this application relates to an electronic device, such as... Figure 9 The device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the steps of the following method: The inspection robot collects data for each wheel. The collected data includes a first distance, a first angle, and a robot tilt angle at each moment. The first distance is the vertical distance between the wheel's measured point and the reference surface. The first angle is the angle between the wheel's measured point and the straight line where the inspection robot is located and the reference surface. The reference surface is the plane perpendicular to the direction of the inspection robot's movement. For the collected data of each wheel, based on the robot tilt angle, the first distance and the first angle corresponding to the same moment are corrected to obtain the second distance and the second angle respectively. The second distance is the vertical distance of the wheel test point relative to the preset ideal surface, and the second angle is the angle between the wheel test point and the straight line where the inspection robot is located and the preset ideal surface. The preset ideal surface is a plane parallel to the side of the wheel, and the robot tilt angle is the angle between the reference surface and the preset ideal surface. Obtain the candidate time when the second distance of each wheel satisfies the preset distance range, and calculate the relative angle difference of the second angle corresponding to every two candidate times; The center position of the wheel is determined based on the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

[0089] In one embodiment, the expression for the second distance is: Dcp=sin(Ap+Q) Dp / sin(Ap) Where Dcp is the second distance, Ap is the first angle, Dp is the first distance, and Q is the robot tilt angle.

[0090] In one embodiment, the expression for the second angle is: Acp = Ap Q Where Acp is the second angle, Ap is the first angle, and Q is the robot tilt angle; When the wheel being measured is located in the forward direction of the inspection robot, then Acp = Ap Q; When the measured point of the vehicle is located in the backward direction of the inspection robot's position, then Acp = Ap Q.

[0091] In one embodiment, the processor, when executing a computer program, also performs the following steps: The center position of the wheel is determined to be the midpoint between the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

[0092] In one embodiment, the expression for the center position of the wheel is: X c X i-1 +(X) i -X i-1 ) / 2 Among them, X c X is the coordinate point of the center position of the wheel; i-1 Let X be the coordinates of the inspection robot corresponding to one of the candidate times; i Let be the coordinates of the inspection robot corresponding to another candidate time.

[0093] In one embodiment, the processor, when executing a computer program, also performs the following steps: Acquire wheel positioning data, which includes the time when the wheel was identified and the wheel's position information at each time. For each wheel, from the moment it is first detected to the moment it is last detected, the inspection robot is driven to collect data from each wheel at a preset sampling frequency.

[0094] In this embodiment, by correcting the first distance and first angle obtained based on the reference surface, a second distance and second angle based on a preset ideal surface are obtained. The center position of the wheel is determined according to the position of the inspection robot at the selected time when the second distance of the same wheel meets the preset distance range. This method has low requirements for the robot's computing performance. The wheel can be accurately positioned after the hardware sensor collects the data, which has high real-time performance. It is also convenient to quickly identify problems in the axis setting process based on the collected data output by the sensor, and the system has good maintainability.

[0095] The memory and processor are connected via a bus, which can include any number of interconnecting buses and bridges, connecting various circuits of one or more processors and memories. The bus can also connect various other circuits, such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and will not be described further herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by the processor is transmitted over the wireless medium via an antenna, which further receives data and transmits it to the processor.

[0096] The processor manages the bus and general processing, and also provides various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory is used to store data used by the processor during operation.

[0097] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic component, for executing the methods in the above embodiments.

[0098] Example 6 Another embodiment of this application relates to a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the steps of the following method: The inspection robot collects data for each wheel. The collected data includes a first distance, a first angle, and a robot tilt angle at each moment. The first distance is the vertical distance between the wheel's measured point and the reference surface. The first angle is the angle between the wheel's measured point and the straight line where the inspection robot is located and the reference surface. The reference surface is the plane perpendicular to the direction of the inspection robot's movement. For the collected data of each wheel, based on the robot tilt angle, the first distance and the first angle corresponding to the same moment are corrected to obtain the second distance and the second angle respectively. The second distance is the vertical distance of the wheel test point relative to the preset ideal surface, and the second angle is the angle between the wheel test point and the straight line where the inspection robot is located and the preset ideal surface. The preset ideal surface is a plane parallel to the side of the wheel, and the robot tilt angle is the angle between the reference surface and the preset ideal surface. Obtain the candidate time when the second distance of each wheel satisfies the preset distance range, and calculate the relative angle difference of the second angle corresponding to every two candidate times; The center position of the wheel is determined based on the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

[0099] In one embodiment, the expression for the second distance is: Dcp=sin(Ap+Q) Dp / sin(Ap) Where Dcp is the second distance, Ap is the first angle, Dp is the first distance, and Q is the robot tilt angle.

[0100] In one embodiment, the expression for the second angle is: Acp = Ap Q Where Acp is the second angle, Ap is the first angle, and Q is the robot tilt angle; When the wheel being measured is located in the forward direction of the inspection robot, then Acp = Ap Q; When the measured point of the vehicle is located in the backward direction of the inspection robot's position, then Acp = Ap Q.

[0101] In one embodiment, when the computer program is executed by a processor, it also performs the following steps: The center position of the wheel is determined to be the midpoint between the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

[0102] In one embodiment, the expression for the center position of the wheel is: X c X i-1 +(X) i -X i-1 ) / 2 Among them, X c X is the coordinate point of the center position of the wheel; i-1Let X be the coordinates of the inspection robot corresponding to one of the candidate times; i Let be the coordinates of the inspection robot corresponding to another candidate time.

[0103] In one embodiment, when the computer program is executed by a processor, it also performs the following steps: Acquire wheel positioning data, which includes the time when the wheel was identified and the wheel's position information at each time. For each wheel, from the moment it is first detected to the moment it is last detected, the inspection robot is driven to collect data from each wheel at a preset sampling frequency.

[0104] In this embodiment, by correcting the first distance and first angle obtained based on the reference surface, a second distance and second angle based on a preset ideal surface are obtained. The center position of the wheel is determined according to the position of the inspection robot at the selected time when the second distance of the same wheel meets the preset distance range. This method has low requirements for the robot's computing performance. The wheel can be accurately positioned after the hardware sensor collects the data, which has high real-time performance. It is also convenient to quickly identify problems in the axis setting process based on the collected data output by the sensor, and the system has good maintainability.

[0105] That is, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0106] Computer-readable storage media may also store at least one computer-executable program / instruction, such as computer-readable instructions. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above can be performed.

[0107] In addition, the computer device may include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (e.g., keyboard, mouse, speakers, etc.).

[0108] The processor can communicate with external devices via the I / O bus through wired or wireless networks.

[0109] Those skilled in the art will understand that the above embodiments are specific embodiments for implementing this application, and in practical applications, various changes can be made to them in form and detail without departing from the spirit and scope of this application.

Claims

1. A method for fixing the axle of a wheel, characterized in that, include: The inspection robot collects data for each wheel. The collected data includes a first distance, a first angle, and a robot tilt angle at each moment. The first distance is the vertical distance between the wheel's measured point and the reference surface. The first angle is the angle between the wheel's measured point and the straight line where the inspection robot is located and the reference surface. The reference surface is the plane perpendicular to the direction of the inspection robot's movement. For the collected data of each wheel, based on the robot tilt angle, the first distance and the first angle corresponding to the same moment are corrected to obtain the second distance and the second angle respectively. The second distance is the vertical distance of the wheel test point relative to the preset ideal surface, and the second angle is the angle between the wheel test point and the straight line where the inspection robot is located and the preset ideal surface. The preset ideal surface is a plane parallel to the side of the wheel, and the robot tilt angle is the angle between the reference surface and the preset ideal surface. Obtain the candidate time when the second distance of each wheel satisfies the preset distance range, and calculate the relative angle difference of the second angle corresponding to every two candidate times; The center position of the wheel is determined based on the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

2. The wheel axle fixing method according to claim 1, characterized in that, The expression for the second distance is: Dcp=sin(Ap+Q) Dp / sin(Ap) Where Dcp is the second distance, Ap is the first angle, Dp is the first distance, and Q is the robot tilt angle.

3. The wheel axle fixing method according to claim 1, characterized in that, The expression for the second angle is: Acp = Ap Q Where Acp is the second angle, Ap is the first angle, and Q is the robot tilt angle; When the wheel being measured is located in the forward direction of the inspection robot, then Acp = Ap Q; When the measured point of the vehicle is located in the backward direction of the inspection robot's position, then Acp = Ap Q.

4. The wheel axle fixing method according to claim 1, characterized in that, The step of determining the center position of the wheel based on the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference includes: The center position of the wheel is determined to be the midpoint between the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

5. The wheel axle fixing method according to claim 4, characterized in that, The expression for the center position of the wheel is: X c X i-1 +(X i -X i-1 ) / 2 Among them, X c X is the coordinate point of the center position of the wheel; i-1 Let X be the coordinates of the inspection robot corresponding to one of the candidate times; i Let be the coordinates of the inspection robot corresponding to another candidate time.

6. The wheel axle fixing method according to claim 1, characterized in that, The method further includes: Acquire wheel positioning data, which includes the time when the wheel was identified and the wheel's position information at each time. For each wheel, from the moment it is first detected to the moment it is last detected, the inspection robot is driven to collect data from each wheel at a preset sampling frequency.

7. A wheel axle fixing device, characterized in that, include: The acquisition module is used to acquire the data collected by the inspection robot for each wheel. The data includes a first distance, a first angle and a robot tilt angle at each moment. The first distance is the vertical distance of the wheel measurement point relative to the reference surface. The first angle is the angle between the wheel measurement point and the straight line where the inspection robot is located and the reference surface. The reference surface is the vertical plane of the inspection robot's forward direction. The correction module is used to correct the first distance and first angle corresponding to the same moment for each wheel based on the robot tilt angle, and obtain a second distance and a second angle respectively. The second distance is the vertical distance of the wheel test point relative to the preset ideal surface, and the second angle is the angle between the wheel test point and the straight line where the inspection robot is located and the preset ideal surface. The preset ideal surface is a plane parallel to the side of the wheel, and the robot tilt angle is the angle between the reference surface and the preset ideal surface. The calculation module is used to obtain the candidate time when the second distance of each wheel satisfies the preset distance range, and to calculate the relative angle difference of the second angle corresponding to each two candidate times; The axis-fixing module is used to determine the center position of the wheel based on the positions of the inspection robot corresponding to the two candidate times with the smallest relative angle difference.

8. An inspection robot, characterized in that, It includes a guided vehicle body, and a reflective photoelectric sensor, a laser profilometer, an tilt sensor, and a trigger plate installed on the guided vehicle body; The reflective photoelectric sensor is installed on the side of the guided vehicle near the wheels and is used for coarse positioning of the wheels. The trigger plate is used to activate when the reflective photoelectric sensor detects a wheel, and simultaneously trigger the laser profiler and tilt sensor; The laser profilometer is installed on the side of the guide vehicle near the wheels and is used to collect distance data of the guide vehicle body relative to the vehicle. The tilt sensor is used to collect the tilt angle of the guide vehicle body relative to an ideal surface, which is a plane parallel to the vertical direction of the wheel position.

9. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the wheel axle fixing method as described in any one of claims 1 to 6.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the wheel axle fixing method according to any one of claims 1 to 6.

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