Railway track collaborative flaw detection method based on double mobile robots

Abstract

The invention discloses a railway track collaborative flaw detection method based on double mobile robots. An existing track flaw detection method cannot meet the railway track detection requirement. Equipment adopted by the collaborative flaw detection method comprises double-mobile-robot track flaw detection equipment, a data processing and analyzing terminal and a main control system, the double mobile robots are responsible for cooperatively performing flaw detection operation on a railway track; the main control system is used for uniformly planning and controlling collaborative operation of the double robots; the data transmission module is responsible for transmitting flaw detection data of the double robots to a processing center in real time for subsequent processing and analysis; and the data processing and analyzing terminal is used for processing and analyzing flaw detection data of the double robots and identifying defects on the railway track. According to the invention, comprehensive and meticulous detection of the railway track is realized, the flaw detection efficiency and accuracy are improved, and the maintenance cost and safety risk are reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of railway track maintenance, and in particular relates to a railway track collaborative flaw detection method based on dual mobile robots. Background Art

[0002] During the operation of trains, the tracks are subject to various alternating loads such as friction, extrusion, bending and impact, as well as various environmental factors such as temperature changes and current corrosion, which can easily cause track collapse, side wear, corrugation and peeling, which seriously threaten the safety of vehicles and people. With the rapid development of my country's rail transit industry, track flaw detection operations urgently need to develop towards unmanned, lightweight and intelligent.

[0003] At present, track flaw detection is mainly carried out by the comprehensive inspection vehicle of the inspection vehicle group under the high-speed railway inspection center for initial inspection (the inspection cycle is twice a month), and the flaw detection workshop under the engineering section uses flaw detection instruments, such as track inspection instruments, track flaw detectors, track weld flaw detectors, etc., for re-inspection operations (the annual number of flaw detections is divided into 5 to 10 times according to the different annual total quality). The line geometric parameters are mainly inspected by the line workshop under the engineering section using hand-push inspection instruments (the inspection cycle is not less than once a month).

[0004] The existing heavy-duty rail comprehensive inspection vehicles have high operating costs and long maintenance cycles, and cannot meet the needs of daily inspection work; light rail comprehensive inspection vehicles can continue to be optimized in the fields of unmanned and lightweight; manual inspection needs to be carried out by different work groups, and the demand for on-site workers is large, the labor cost is high, and the inspection speed is slow (2-3km / h), and the line inspection efficiency is low; traditional separation robots can only be applied to short-distance, straight tracks (such as lifting machinery tracks), and cannot meet the requirements of railway track inspection. When encountering complex line conditions such as turnouts, there is a risk of falling off the track, affecting driving safety. Summary of the invention

[0005] In order to make up for the shortcomings of the prior art, the present invention provides a railway track collaborative flaw detection method based on dual mobile robots, which utilizes the collaborative operation of the dual mobile robots to achieve comprehensive and detailed inspection of the railway track, improve flaw detection efficiency and accuracy, and reduce maintenance costs and safety risks.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] A railway track collaborative flaw detection method based on dual mobile robots, characterized in that:

[0008] The equipment used in the collaborative flaw detection method includes dual mobile robot rail flaw detection equipment, a data processing and analysis terminal, and a main control system; the dual mobile robots are responsible for collaborative flaw detection operations on the railway track;

[0009] The main control system is used to uniformly plan and control the collaborative operation of the dual robots; it is responsible for transmitting the dual robots' flaw detection data to the processing center in real time for subsequent processing and analysis;

[0010] The data processing and analysis terminal is used to process and analyze the flaw detection data of the dual robots and identify defects on the railway track;

[0011] Furthermore, the dual mobile robot track flaw detection equipment includes a shell, a motor, a driving wheel, a detection device, and a main control system.

[0012] Furthermore, the detection equipment includes a track surface damage detection equipment and a track geometry parameter detection equipment. The track surface damage detection equipment is arranged at the bottom of the whole machine and close to the track surface. The track geometry parameter detection equipment requires two robots to work together and needs to be installed on the whole machine close to the center line of the line.

[0013] Furthermore, the main control system includes a control system, a communication device, and a positioning device.

[0014] Furthermore, the data processing and analysis terminal fuses the flaw detection data of the dual robots to improve the integrity and accuracy of the data; defect identification: using advanced algorithms and models to process and analyze the fused data to identify defects on the railway track; result display: the identification results are displayed to users in the form of graphics, reports, etc. to facilitate user understanding and decision-making.

[0015] Further, the following steps are included:

[0016] Step 1: Initialization and preparation;

[0017] Step 2: Start the dual robots and make them walk in a synchronous control mode;

[0018] Step 3: During the flaw detection process, the dual robots first use ultrasonic sensors to scan the railway track, and determine whether there are defects on the track by receiving the reflected ultrasonic signals; then use the magnetic particle flaw detection device to apply magnetic powder on the railway track, and use the magnetic field to make the magnetic powder gather at the defect, so as to identify the location and shape of the defect; finally, use the eddy current flaw detection sensor to scan the railway track, and determine whether there are other types of defects on the track by detecting the changes in eddy current;

[0019] The dual robots collect flaw detection data in real time and transmit it to the main control system for subsequent processing and analysis; the collected flaw detection data is transmitted to the data processing and analysis system for processing and analysis; the data is first pre-processed, and then the flaw detection data of the dual robots are fused; then the fused data is processed and analyzed to identify defects on the railway track; finally, the identification results are displayed to users in the form of graphics, reports, etc., to facilitate user understanding and decision-making; at the same time, the defects are marked and classified according to the identification results to provide guidance for subsequent maintenance and processing.

[0020] Further, in step three, the dual mobile robot rail flaw detection device may receive the first instruction and the second instruction from the data processing and analysis terminal through the main control system;

[0021] The dual mobile robot rail flaw detection device measures the relative positions of the dual mobile robot rail flaw detection device in response to the first instruction, and determines that the initial positions of the dual mobile robot rail flaw detection device are horizontally aligned on the dual rails; the dual mobile robot rail flaw detection device controls the rail flaw detection device to collect a first image during the sliding process on the rail in response to the second instruction, and the first image includes image information of the rail surface and the vicinity of the line;

[0022] The rail flaw detection equipment uploads the collected information to the data processing and analysis terminal through the main control system, which makes it easier for maintenance personnel to understand the entire flaw detection process and analyze and trace the damage of the rails;

[0023] Based on the first image, the damage condition of the track, the track geometric parameters and the surrounding environment of the line are analyzed.

[0024] Further, in step three,

[0025] The main control system includes a control system, a communication device, and a positioning device; the communication device can accept the first instruction and the second instruction transmitted by the user to the main control system through the digital processing and analysis terminal, and send them to the control system; the positioning device can respond to the first instruction, can obtain the initial position of the track flaw detection device, and send it to the control module; the control module can control the sliding module to drive the track flaw detection device to slide on the track according to the first spacing and the initial position; at the same time, the control module can respond to the second instruction, control the visual sensor to collect a first image during the sliding of the track flaw detection device on the track, and the first image may include image information of the track and the tunnel where the track is located; the control module can analyze the damage condition of the track based on the first image.

[0026] Furthermore, in step three, the control system includes a synchronous control subsystem and a collision avoidance subsystem; the synchronous control strategy is used to ensure that the dual robots maintain high consistency during walking and flaw detection, and the synchronous control method is specifically as follows:

[0027] Time synchronization: through timestamp or time synchronization protocol, ensure that the two robots perform the same operation at the same time point; position synchronization: by real-time monitoring of the position information of the two robots, ensure that they perform flaw detection operations at the same position; speed synchronization: by adjusting the walking speed of the two robots, ensure that they travel the same distance in the same time period.

[0028] Furthermore, in step 3, the collision detection and avoidance strategy is used to ensure that the dual robots do not collide with obstacles during the collaborative operation; the collision detection and avoidance method is specifically as follows:

[0029] Sensor-based collision detection: Install sensors to monitor the relative position and posture between the two robots in real time. Once a potential collision risk is detected, take appropriate measures to avoid it immediately. Vision-based collision detection: Use visual sensors to monitor the surrounding environment of the two robots in real time, and use image processing algorithms to identify potential collision risks.

[0030] Beneficial effects of the present invention:

[0031] 1) The railway track collaborative flaw detection method based on dual mobile robots of the present invention improves flaw detection efficiency and accuracy, and reduces maintenance costs and safety risks;

[0032] 2) The main control system of the present invention adopts synchronous control to ensure that the dual mobile robots maintain a high degree of consistency during walking and flaw detection to avoid collision or interference; the operating status of the dual robots, including position, speed, load, etc., is monitored in real time to ensure operation safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 The present invention adopts the equipment structure diagram;

[0034] Figure 2 Shown is a diagram of the robot on track of the present invention;

[0035] Figure 3 It is a structural schematic diagram of a dual mobile robot rail flaw detection device;

[0036] Figure 4 A way for the robot to pass through areas with obstacles. DETAILED DESCRIPTION

[0037] The present invention is described in detail below in conjunction with specific implementation modes.

[0038] Railway tracks have many types of defects (such as cracks, wear, corrosion, etc.), and the terrain is complex and changeable (such as bridges, tunnels, curves, etc.), so there are many difficulties in using traditional flaw detection methods. In order to improve the efficiency and accuracy of flaw detection and reduce maintenance costs and safety risks, the railway track collaborative flaw detection method based on dual mobile robots provided by the present invention is adopted.

[0039] like Figure 1 As shown, the equipment used in the collaborative flaw detection method includes dual mobile robot track flaw detection equipment, data processing and analysis terminal, and main control system;

[0040] 1) The dual mobile robots are the main execution equipment of the present invention, responsible for collaborative flaw detection on the railway track; the dual mobile robot track flaw detection equipment includes a shell, a motor, a driving wheel, a detection device, and a main control system. The shell is made of low-density, high-strength, and high-toughness materials; the motor is driven by electricity + solar energy; the driving wheel: the whole machine is driven by four sets of wheels and can be retracted into the shell.

[0041] The dual mobile robot has the following features: High-precision positioning: the positioning technology is used to ensure the accurate walking and positioning of the robot on the railway track; Stable walking ability: the walking mechanism adapted to the characteristics of the railway track ensures the stable walking of the robot in various complex environments. Figure 2 It shows the on-orbit status of the robot; various sensors: including laser rangefinders, visual sensors, etc., are used to monitor the robot's surrounding environment in real time to ensure operational safety. Figure 3 One of the structural schematic diagrams of the dual mobile robot rail flaw detection equipment is shown.

[0042] The detection equipment includes track surface damage detection equipment and track geometry parameter detection equipment. The track surface damage detection equipment is arranged at the bottom of the whole machine and close to the track surface. The track geometry parameter detection equipment requires two robots to work together and needs to be installed on the whole machine close to the center line of the line.

[0043] 2) The main control system is used to unify the planning and control of the collaborative operation of the dual robots; it is responsible for transmitting the detection data of the dual robots to the processing center in real time for subsequent processing and analysis; the main control system includes control systems, communication equipment, and positioning equipment. The main control system uses synchronous control to ensure that the dual mobile robots maintain a high degree of consistency during walking and flaw detection to avoid collisions or interference; it monitors the operating status of the dual robots in real time, including position, speed, load, etc., to ensure operational safety.

[0044] 3) The data processing and analysis terminal is used to process and analyze the flaw detection data of the dual robots and identify defects on the railway track; the data processing and analysis terminal fuses the flaw detection data of the dual robots to improve the integrity and accuracy of the data; defect identification: using advanced algorithms and models, the fused data is processed and analyzed to identify defects on the railway track; result display: the identification results are displayed to the user in the form of graphics, reports, etc., to facilitate user understanding and decision-making.

[0045] The present invention provides a railway track collaborative flaw detection method based on dual mobile robots, comprising the following steps:

[0046] Step 1: Initialization and preparation;

[0047] Initialize the dual robots, including configuration parameters, sensor calibration, etc., to ensure that the robots can work normally; check the integrity and functionality of the flaw detection equipment and other necessary accessories, including ultrasonic sensors, magnetic particle flaw detection devices, eddy current flaw detection sensors, etc., to ensure that no faults occur during the operation; set up safety warning signs around the operating area to ensure that no safety hazards are caused to personnel and equipment during the operation.

[0048] Step 2: Start the dual robots and make them walk in a synchronous control mode;

[0049] During the walking process, high-precision navigation technology is used to accurately position the dual mobile robots, and sensors are used to monitor the position and posture of the dual robots in real time. According to the real-time monitoring results, the walking speed and position of the dual robots are dynamically adjusted to ensure that they can smoothly reach the predetermined detection points. When encountering complex terrain (such as bridges, tunnels, switches, etc.), the walking strategy and parameters are adjusted to ensure that the dual robots can walk stably and avoid safety accidents such as collisions or derailment.

[0050] Step 3: During the flaw detection process, the dual robots first use ultrasonic sensors to scan the railway track, and determine whether there are defects on the track by receiving the reflected ultrasonic signals; then use the magnetic particle flaw detection device to apply magnetic powder on the railway track, and use the magnetic field to make the magnetic powder gather at the defect, so as to identify the location and shape of the defect; finally, use the eddy current flaw detection sensor to scan the railway track, and determine whether there are other types of defects on the track by detecting the changes in eddy current;

[0051] At the same time, through the cooperation of the two robots, that is, the transmission and reception of signals, the displacement of the two mobile robots is kept synchronized, and dynamic detection of track height, track gauge, level, rule change rate and other parameters is achieved. The two robots collect flaw detection data in real time, including ultrasonic signals, magnetic powder aggregation, eddy current changes, synchronous signal data, etc., and transmit them to the main control system for subsequent processing and analysis;

[0052] The collected flaw detection data is transmitted to the data processing and analysis system for processing and analysis; first, the data is preprocessed, including denoising, filtering, calibration, etc., to improve the accuracy and reliability of the data; then the flaw detection data of the dual robots are fused to improve the integrity and accuracy of the data; in the data fusion process, advanced algorithms and models are used to process and analyze the data to ensure that the fused data can accurately reflect the actual situation of the railway track. Then, advanced algorithms and models are used to process and analyze the fused data to identify defects on the railway track; in the defect identification process, machine learning algorithms are used to classify and identify defects, which improves the accuracy and efficiency of identification.

[0053] Finally, the recognition results are presented to users in the form of graphics, reports, etc., which is convenient for users to understand and make decisions; at the same time, defects are marked and classified according to the recognition results to provide guidance for subsequent maintenance and processing. According to the recognition results of the data processing and analysis system, the defect information is fed back to relevant personnel so that corresponding disposal measures can be taken. Specifically, it includes marking and classifying defects, and proposing corresponding maintenance suggestions and treatment plans. Maintenance personnel repair and treat the railway tracks according to the defect information. During the treatment process, appropriate maintenance methods and tools are used to repair or replace defects to ensure the safety and reliability of the railway tracks. Track and monitor the repaired railway tracks to ensure that the maintenance effect meets the requirements. During the tracking and monitoring process, dual robots and flaw detection equipment are used to regularly inspect and test the repaired tracks to ensure the normal operation and safety of the tracks.

[0054] In step three, the dual mobile robot track flaw detection equipment can receive the first instruction and the second instruction from the data processing and analysis terminal through the main control system; the dual mobile robot track flaw detection equipment responds to the first instruction, measures the relative position of the dual mobile robot track flaw detection equipment, and determines that the initial position of the dual mobile robot track flaw detection equipment is horizontally aligned on the dual tracks; the dual mobile robot track flaw detection equipment responds to the second instruction, controls the track flaw detection equipment to collect a first image during the sliding process on the track, and the first image includes image information of the track surface and the vicinity of the line; the track flaw detection equipment uploads the collected information to the data processing and analysis terminal through the main control system, so that maintenance personnel can understand the entire flaw detection process and analyze and trace the damage of the track; based on the first image, analyze the damage of the track (such as track crushing, side wear, corrugation and peeling damage), track geometric parameters (track gauge, horizontal change rate, etc.) and the surrounding environment of the line.

[0055] In step three, the main control system includes a control system, a communication device, and a positioning device; the communication device can accept the first instruction and the second instruction transmitted by the user to the main control system through the digital processing and analysis terminal, and send them to the control system; the positioning device can respond to the first instruction, can obtain the initial position of the track flaw detection equipment, and send it to the control module; the control module can control the sliding module to drive the track flaw detection equipment to slide on the track according to the first spacing and the initial position; at the same time, the control module can respond to the second instruction, control the visual sensor to collect a first image during the sliding of the track flaw detection equipment on the track, and the first image may include image information of the track and the tunnel where the track is located; the control module can analyze the damage condition of the track based on the first image.

[0056] In step 3, the control system includes a synchronous control subsystem and a collision avoidance subsystem; the synchronous control strategy is used to ensure that the dual robots maintain high consistency during walking and flaw detection. The specific synchronous control method is as follows:

[0057] Time synchronization: through timestamp or time synchronization protocol, ensure that the two robots perform the same operation at the same time point; position synchronization: by real-time monitoring of the position information of the two robots, ensure that they perform flaw detection operations at the same position; speed synchronization: by adjusting the walking speed of the two robots, ensure that they travel the same distance in the same time period.

[0058] The collision detection and avoidance strategy is used to ensure that the two robots do not collide with obstacles during collaborative operation; the specific collision detection and avoidance methods are as follows:

[0059] Sensor-based collision detection: Install sensors to monitor the relative position and posture between the two robots in real time. Once a potential collision risk is detected, take appropriate measures to avoid it immediately. Vision-based collision detection: Use visual sensors to monitor the surrounding environment of the two robots in real time, and use image processing algorithms to identify potential collision risks.

[0060] The positioning module can be implemented through the Beidou navigation system. Since the positioning module can locate the real-time position of the track flaw detection equipment, the control module can also control the user equipment (i.e., the prompt device) to output the first prompt information after analyzing the damage condition of the track based on the first image. The first prompt information can indicate the damaged position of the track. In this way, the damaged position corresponding to the damaged part of the track is displayed to the user in a timely manner, which is convenient for maintenance personnel to carry out maintenance in time, and can effectively avoid further deterioration of track damage.

[0061] Figure 4It shows how the machine can pass through areas with obstacles. For example, in the turnout rut area, there are four sets of drive wheels, which are installed in groups on the front and rear sides of the vehicle body, and the positions of the outer wheels and rims are changed by the lifting device. Image sensors are installed in the front and rear rows of the vehicle to detect whether it has entered the turnout rut area. Distance sensors are installed on the four drive wheel axles to detect whether the current wheel group has passed the turnout area. When it is about to enter the turnout rut area, the control system controls the whole machine to slow down to a stop state, and then raises the outer wheel and rim of the No. 1 wheel group, and its inner wheel and rim are fixed according to the No. 2, 3, and 4 wheel devices and drive the whole machine to travel. When a wheel group passes the turnout, the control system resets the outer supporting wheel and rim according to the distance sensor data until the whole machine passes.

[0062] The content of the present invention is not limited to the embodiments listed, and any equivalent changes made to the technical solution of the present invention by ordinary technicians in this field after reading the description of the present invention are covered by the claims of the present invention.

Claims

1. A railway track collaborative flaw detection method based on dual mobile robots, characterized in that: The equipment used in the collaborative flaw detection method includes dual mobile robot rail flaw detection equipment, a data processing and analysis terminal, and a main control system; the dual mobile robots are responsible for collaborative flaw detection operations on the railway track; The main control system is used to uniformly plan and control the collaborative operation of the dual robots; it is responsible for transmitting the dual robots' flaw detection data to the processing center in real time for subsequent processing and analysis; The data processing and analysis terminal is used to process and analyze the flaw detection data of the dual robots and identify defects on the railway tracks.

2. The railway track collaborative flaw detection method based on dual mobile robots according to claim 1 is characterized in that: The dual mobile robot track flaw detection device comprises a housing, a motor, a driving wheel, a detection device, and a main control system.

3. The railway track collaborative flaw detection method based on dual mobile robots according to claim 2 is characterized in that: The detection equipment includes a track surface damage detection equipment and a track geometry parameter detection equipment. The track surface damage detection equipment is arranged at the bottom of the whole machine and close to the track surface. The track geometry parameter detection equipment requires two robots to work together and needs to be installed on the whole machine close to the center line of the line.

4. The railway track collaborative flaw detection method based on dual mobile robots according to claim 3 is characterized in that: The main control system includes a control system, a communication device, and a positioning device.

5. The railway track collaborative flaw detection method based on dual mobile robots according to claim 4 is characterized in that: The data processing and analysis terminal fuses the flaw detection data of the dual robots to improve the integrity and accuracy of the data; defect identification: uses advanced algorithms and models to process and analyze the fused data to identify defects on the railway track; result display: displays the identification results to users in the form of graphics, reports, etc. to facilitate user understanding and decision-making.

6. The railway track collaborative flaw detection method based on dual mobile robots according to claim 5 is characterized in that: The steps include: Step 1: Initialization and preparation; Step 2: Start the dual robots and make them walk in a synchronous control mode; Step 3: During the flaw detection process, the dual robots first use ultrasonic sensors to scan the railway track, and determine whether there are defects on the track by receiving the reflected ultrasonic signals; then use the magnetic particle flaw detection device to apply magnetic powder on the railway track, and use the magnetic field to make the magnetic powder gather at the defect, so as to identify the location and shape of the defect; finally, use the eddy current flaw detection sensor to scan the railway track, and determine whether there are other types of defects on the track by detecting the changes in eddy current; The dual robots collect flaw detection data in real time and transmit it to the main control system for subsequent processing and analysis; the collected flaw detection data is transmitted to the data processing and analysis system for processing and analysis; the data is first pre-processed, and then the flaw detection data of the dual robots are fused; then the fused data is processed and analyzed to identify defects on the railway track; finally, the identification results are displayed to users in the form of graphics, reports, etc., to facilitate user understanding and decision-making; at the same time, the defects are marked and classified according to the identification results to provide guidance for subsequent maintenance and processing.

7. The railway track collaborative flaw detection method based on dual mobile robots according to claim 6 is characterized in that: In step three, the dual mobile robot rail flaw detection device may receive the first instruction and the second instruction from the data processing and analysis terminal through the main control system; The dual mobile robot rail flaw detection device measures the relative positions of the dual mobile robot rail flaw detection device in response to the first instruction, and determines that the initial positions of the dual mobile robot rail flaw detection device are horizontally aligned on the dual rails; the dual mobile robot rail flaw detection device controls the rail flaw detection device to collect a first image during the sliding process on the rail in response to the second instruction, and the first image includes image information of the rail surface and the vicinity of the line; The rail flaw detection equipment uploads the collected information to the data processing and analysis terminal through the main control system, which makes it easier for maintenance personnel to understand the entire flaw detection process and analyze and trace the damage of the rails; Based on the first image, the damage condition of the track, the track geometric parameters and the surrounding environment of the line are analyzed.

8. The railway track collaborative flaw detection method based on dual mobile robots according to claim 7 is characterized in that: In step three, The main control system includes a control system, a communication device, and a positioning device; the communication device can accept the first instruction and the second instruction transmitted by the user to the main control system through the digital processing and analysis terminal, and send them to the control system; the positioning device can respond to the first instruction, can obtain the initial position of the track flaw detection device, and send it to the control module; the control module can control the sliding module to drive the track flaw detection device to slide on the track according to the first spacing and the initial position; at the same time, the control module can respond to the second instruction, control the visual sensor to collect a first image during the sliding of the track flaw detection device on the track, and the first image may include image information of the track and the tunnel where the track is located; the control module can analyze the damage condition of the track based on the first image.

9. The railway track collaborative flaw detection method based on dual mobile robots according to claim 8, characterized in that: In step 3, the control system includes a synchronous control subsystem and a collision avoidance subsystem; the synchronous control strategy is used to ensure that the dual robots maintain high consistency during walking and flaw detection. The specific synchronous control method is as follows: Time synchronization: through timestamp or time synchronization protocol, ensure that the two robots perform the same operation at the same time point; position synchronization: by real-time monitoring of the position information of the two robots, ensure that they perform flaw detection operations at the same position; speed synchronization: by adjusting the walking speed of the two robots, ensure that they travel the same distance in the same time period.

10. The railway track collaborative flaw detection method based on dual mobile robots according to claim 9, characterized in that: In step 3, the collision detection and avoidance strategy is used to ensure that the two robots do not collide with obstacles during the collaborative operation; the specific collision detection and avoidance method is: Sensor-based collision detection: Install sensors to monitor the relative position and posture between the two robots in real time. Once a potential collision risk is detected, take appropriate measures to avoid it immediately. Vision-based collision detection: Use visual sensors to monitor the surrounding environment of the two robots in real time, and use image processing algorithms to identify potential collision risks.

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