Railway track cooperative flaw detection method based on double mobile robots

Abstract

The application discloses a kind of railway track cooperative flaw detection methods based on double mobile robots.The existing track flaw detection method cannot satisfy the railway track detection requirement.The cooperative flaw detection method of the application adopts equipment including double mobile robot track flaw detection equipment, data processing and analysis terminal, main control system;Double mobile robot is responsible for the flaw detection operation on railway track in cooperation;Main control system is used for unified planning and control double robot cooperative operation;Responsible for the real-time transmission of double robot flaw detection data to processing center, so as to carry out subsequent processing and analysis;Data processing and analysis terminal is used for processing and analyzing the flaw detection data of double robot, and identifying the defects on railway track.The application realizes comprehensive and detailed detection of railway track, improves flaw detection efficiency and accuracy, and reduces maintenance cost and safety risk.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of railway track maintenance, and particularly relates to a railway track cooperative flaw detection method based on double mobile robots. BACKGROUND

[0002] During train operation, the track is affected by various alternating loads such as friction, extrusion, bending and impact, and various environmental factors such as temperature changes and current corrosion, which can easily cause track crushing, side grinding, wave grinding and peeling, etc., seriously threatening the safety of vehicles and people. With the rapid development of China's rail transportation industry, track flaw detection operations need to develop towards unmanned, lightweight and intelligent.

[0003] Currently, track flaw detection is mainly carried out by the comprehensive detection vehicle of the detection vehicle group under the high-speed rail detection center (inspection period is 2 times per month), and the flaw detection instrument such as track inspection instrument, track flaw detection instrument and track weld flaw detection instrument is used by the flaw detection workshop under the maintenance section to carry out re-inspection operation (annual flaw detection frequency is 5-10 times according to different annual total mass); the line geometry parameters are mainly inspected by the line workshop under the maintenance section using the hand-push type inspection instrument (inspection period is not less than 1 time per month).

[0004] The existing heavy track comprehensive detection vehicle has high operation cost and long maintenance period, and cannot meet the daily inspection work; the lightweight track comprehensive detection vehicle can continue to be optimized in the fields of unmanned and lightweight; manual detection needs to be carried out by different work groups, and a large number of on-site operation personnel are needed, which has high labor cost and slow detection speed (2-3km / h), and low line detection efficiency; the traditional separated robot can only be applied to short-range and straight track (such as hoisting machinery track), and cannot meet the requirements of railway track detection. When encountering complex line conditions such as turnout, there is a risk of falling off the track, which affects the safety of train operation. SUMMARY

[0005] In order to make up for the shortcomings of the prior art, the present application provides a railway track cooperative flaw detection method based on double mobile robots, which realizes comprehensive and detailed detection of the railway track by using double mobile robots for cooperative operation, improves the flaw detection efficiency and accuracy, and reduces the maintenance cost and safety risk.

[0006] In order to achieve the above purpose, the technical scheme adopted by the present application is as follows:

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

[0008] The equipment used in the cooperative flaw detection method includes a double mobile robot track flaw detection device, a data processing and analysis terminal and a main control system; the double mobile robot is responsible for cooperative flaw detection operation on the railway track;

[0009] The master control system is used for unified planning and control of the cooperative work of the double robots; it is responsible for real-time transmission of the double robots' flaw detection data to the processing center for subsequent processing and analysis;

[0010] The data processing and analysis terminal is used for processing and analyzing the double robots' flaw detection data to identify defects on the railway track;

[0011] Further, the double mobile robot track flaw detection device comprises a shell, a motor, a drive wheel, a detection device, and a master control system.

[0012] Further, the detection device comprises a track surface damage detection device and a track geometric parameter detection device, the track surface damage detection device is arranged at the lower part of the whole machine and close to the track surface, and the track geometric parameter detection device needs the cooperation of the two robots and needs to be installed on the whole machine close to the center line direction of the line.

[0013] Further, the master control system comprises a control system, a communication device, and a positioning device.

[0014] Further, the data processing and analysis terminal fuses the double robots' flaw detection data to improve the completeness and accuracy of the data; defect identification: advanced algorithms and models are used to process and analyze the fused data to identify defects on the railway track; result display: the identification results are displayed to the user in the form of graphs, reports, etc. for the user to understand and make decisions.

[0015] Further, the method comprises the following steps:

[0016] Step one: initialization and preparation work;

[0017] Step two: start the double robots and walk according to the synchronous control mode;

[0018] Step three: in the flaw detection process, the double robots first scan the railway track using ultrasonic sensors to determine whether there are defects on the track by receiving the reflected ultrasonic signals; then use the magnetic powder flaw detection device to apply magnetic powder on the railway track, use the magnetic field to make the magnetic powder gather at the defect, and thus identify the position and shape of the defect; finally, use the eddy current flaw detection sensor to scan the railway track to determine whether there are other types of defects on the track by detecting the change of the eddy current;

[0019] The double-robot real-time collects flaw detection data and transmits the flaw detection data to the master 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; first, the data is preprocessed, then the flaw detection data of the double-robot is fused; then, the fused data is processed and analyzed to identify defects on the railway track; finally, the identification results are displayed to the user in the form of graphics, reports, etc., for the user to understand and make decisions; 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 double-mobile-robot track flaw detection equipment can receive the first instruction and the second instruction from the data processing and analysis terminal through the master control system;

[0021] The double-mobile-robot track flaw detection equipment measures the relative position of the double-mobile-robot track flaw detection equipment in response to the first instruction to determine that the initial position of the double-mobile-robot track flaw detection equipment is horizontally aligned on the double track; the double-mobile-robot track flaw detection equipment controls the track flaw detection equipment to collect a first image during the sliding process on the track in response to the second instruction, and the first image includes image information of the track surface and the line nearby;

[0022] The track flaw detection equipment uploads the collected information to the data processing and analysis terminal through the master control system, so that the maintenance personnel can understand the whole process of the flaw detection operation and analyze and trace the damage of the track;

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

[0024] Further, in step three,

[0025] The master control system includes a control system, a communication device, and a positioning device; the communication device can receive the first instruction and the second instruction transmitted by the user to the master control system through the digital processing and analysis terminal and send them to the control system; the positioning device can obtain the initial position of the track flaw detection equipment in response to the first instruction 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 distance and the initial position; at the same time, the control module can control the visual sensor to collect a first image during the sliding process of the track flaw detection equipment on the track in response to the second instruction, and the first image can include image information of the track and the tunnel where the track is located; the control module can analyze the damage of the track based on the first image.

[0026] Further, 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 double-robot maintains high consistency during walking and flaw detection, and the synchronous control method is as follows:

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

[0028] Further, in step three, the collision detection and avoidance strategy is used to ensure that the double robots do not collide with obstacles during collaborative operation; The collision detection and avoidance method is specifically:

[0029] Sensor-based collision detection: by installing sensors to monitor the relative position and attitude of the double robots in real time, once potential collision risk is detected, take corresponding measures to avoid; Vision-based collision detection: use visual sensors to monitor the surrounding environment of the double robots in real time, and identify potential collision risks through image processing algorithms.

[0030] The beneficial effects of the present application are:

[0031] 1) The double mobile robot-based railway track collaborative flaw detection method of the present application improves flaw detection efficiency and accuracy, reduces maintenance cost and safety risk;

[0032] 2) The master control system of the present application adopts synchronous control, ensures that the double mobile robots maintain high consistency during walking and flaw detection, avoids collision or interference; Real-time monitoring of the running state of the double robots, including position, speed, load, etc., ensures operation safety. BRIEF DESCRIPTION OF DRAWINGS

[0033] Figure 1 The device structure diagram is used for the present application;

[0034] Figure 2 The robot on-track state diagram is shown in the present application;

[0035] Figure 3 The structure diagram of the double mobile robot track flaw detection device is shown in the present application;

[0036] Figure 4 The robot passes through the obstacle section. DETAILED DESCRIPTION

[0037] The present application will be described in detail below in combination with specific embodiments.

[0038] There are various types of defects (such as cracks, wear, corrosion, etc.) in railway tracks, 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 flaw detection efficiency and accuracy, reduce the maintenance cost and safety risk, the railway track cooperative flaw detection method based on double mobile robots is adopted.

[0039] As shown in Figure 1 The cooperative flaw detection method adopts equipment including double mobile robot track flaw detection equipment, data processing and analysis terminal, and main control system.

[0040] 1) The double mobile robot is the main execution equipment of the application, responsible for cooperative flaw detection operation on the railway track; the double mobile robot track flaw detection equipment includes a shell, a motor, a drive wheel, a detection device, and a main control system. The shell is made of low-density, high-strength, and high-toughness material; the motor is driven by electricity and solar energy; the drive wheel is driven by four groups of wheelsets and can be retracted into the shell.

[0041] The double mobile robot has the following characteristics: high-precision positioning: using positioning technology to ensure accurate walking and positioning of the robot on the railway track; stable walking ability: walking mechanism suitable for the characteristics of the railway track to ensure stable walking of the robot in various complex environments, Figure 2 The robot in the track state is shown; a variety of sensors: including laser range finder, vision sensor, etc., for real-time monitoring of the surrounding environment of the robot to ensure job safety. Figure 3 The structure diagram of the double mobile robot track flaw detection equipment is shown.

[0042] The detection device includes track surface damage detection equipment and track geometric parameter detection equipment. The track surface damage detection equipment is arranged at the lower part of the whole machine and close to the track surface, and the track geometric parameter detection equipment needs the cooperation of two robots and needs to be installed on the machine close to the center line direction of the track.

[0043] 2) The main control system is used for unified planning and control of the cooperative operation of the double robots; responsible for real-time transmission of the flaw detection data of the double robots to the processing center for subsequent processing and analysis; the main control system includes a control system, a communication device, and a positioning device. The main control system adopts synchronous control to ensure that the double mobile robots maintain high consistency during walking and flaw detection to avoid collision or interference; real-time monitoring of the running state of the double robots, including position, speed, load, etc., to ensure job safety.

[0044] 3) Data processing and analysis terminal is used for processing and analyzing the flaw detection data of the dual robots, identifying defects on the railway track; the data processing and analysis terminal fuses the flaw detection data of the dual robots, improving the completeness and accuracy of the data; defect identification: advanced algorithms and models are used to process and analyze the fused data, identifying defects on the railway track; result display: the identification results are displayed to the user in the form of graphics, reports, etc., facilitating user understanding and decision-making.

[0045] The present application is based on a railway track cooperative flaw detection method based on dual mobile robots, comprising the following steps:

[0046] Step one: initialization and preparation work;

[0047] The dual robots are initialized and set, including configuring parameters, calibrating sensors, etc., to ensure that the robots can work normally; the integrity and functionality of the flaw detection equipment and other necessary accessories are checked, including ultrasonic sensors, magnetic powder flaw detection devices, eddy current flaw detection sensors, etc., to ensure that no faults occur during the operation process; safety warning signs are set around the operation area to ensure that no safety hazards occur to personnel and equipment during the operation process.

[0048] Step two: start the dual robots and walk according to the synchronous control mode;

[0049] During walking, high-precision navigation technology is used to accurately position the dual mobile robots, and sensors are used to monitor the position and attitude 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 flaw detection point; when encountering complex terrain (such as bridges, tunnels, turnouts, etc.), the walking strategy and parameters are adjusted to ensure that the dual robots can walk stably and avoid safety accidents such as collision or derailment.

[0050] Step three: during the flaw detection process, the dual robots first use ultrasonic sensors to scan the railway track, and judge whether there are defects on the track by receiving the reflected ultrasonic signals; then use the magnetic powder flaw detection device to apply magnetic powder on the railway track, use the magnetic field to make the magnetic powder gather at the defect, and identify the position and shape of the defect; finally, use the eddy current flaw detection sensor to scan the railway track, and judge whether there are other types of defects on the track by detecting the change of eddy current;

[0051] At the same time, through the cooperation of the two robots, i.e. the emission and reception of signals, the displacement of the dual mobile robots is kept synchronous, and dynamic detection of track height, track gauge, level, gauge change rate, etc. is realized. The dual robots collect flaw detection data in real time, including ultrasonic signals, magnetic powder gathering conditions, eddy current changes, synchronization signal data, etc., and transmit them to the main control system for subsequent processing and analysis;

[0052] The collected defect 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 defect detection data of the dual robot is 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 accurately reflects the actual situation of the railway track. Then the fused data is processed and analyzed using advanced algorithms and models to identify defects on the railway track. In the defect identification process, machine learning algorithms are used to classify and identify defects, improving the accuracy and efficiency of identification.

[0053] Finally, the identification results are displayed to the user in the form of graphs, reports, etc., to facilitate user understanding and decision-making. At the same time, the defects are marked and classified according to the identification results, providing guidance for subsequent maintenance and processing. According to the identification results of the data processing and analysis system, the defect information is fed back to the relevant personnel to take appropriate measures. Specifically, it includes marking and classifying defects, proposing appropriate maintenance recommendations and processing schemes. Maintenance personnel repair and process the railway track according to the defect information. In the processing process, appropriate maintenance methods and tools are used to repair or replace defects to ensure the safety and reliability of the railway track. The repaired railway track is tracked and monitored to ensure that the repair effect meets the requirements. In the tracking and monitoring process, the dual robot and the defect detection equipment are used to regularly check and test the repaired track to ensure the normal operation and safety of the track.

[0054] In step three, the dual mobile robot track defect 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 defect detection equipment measures the relative position of the dual mobile robot track defect detection equipment in response to the first instruction, determines that the initial position of the dual mobile robot track defect detection equipment is horizontally aligned on the double track; the dual mobile robot track defect detection equipment controls the track defect detection equipment to collect the first image during the sliding process on the track in response to the second instruction, the first image includes image information of the track surface and the line nearby; the track defect detection equipment uploads the collected information to the data processing and analysis terminal through the main control system, which is convenient for maintenance personnel to understand the whole process of defect detection operation 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 grinding, wave grinding and peeling), track geometric parameters (track gauge, horizontal change rate, etc.) and line surrounding environment.

[0055] In step three, the main control system includes a control system, a communication device, and a positioning device. The communication device can receive first instructions and second instructions transmitted by the user through the digital processing analysis terminal to the main control system and send them to the control system. The positioning device can obtain the initial position of the track flaw detection device in response to the first instructions 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 distance and the initial position. At the same time, the control module can control the vision sensor to collect a first image during the sliding of the track flaw detection device on the track in response to the second instructions. The first image can include image information of the track and the tunnel where the track is located. The control module can analyze the damage of the track based on the first image.

[0056] 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. The synchronous control method is as follows:

[0057] Time synchronization: Ensure that the dual robots perform the same operation at the same time point through timestamp or time synchronization protocol; Position synchronization: Ensure that the dual robots perform flaw detection operations at the same position by monitoring their position information in real time; Speed synchronization: Adjust the walking speed of the dual robots to ensure that they walk the same distance within the same time period.

[0058] The collision detection and avoidance strategy is used to ensure that the dual robots do not collide with obstacles during collaborative work. The collision detection and avoidance method is as follows:

[0059] Sensor-based collision detection: Real-time monitoring of the relative position and attitude between the dual robots through the installation of sensors, and taking appropriate measures to avoid potential collision risks as soon as they are detected; Vision-based collision detection: Real-time monitoring of the surrounding environment of the dual robots through vision sensors, and identifying potential collision risks through image processing algorithms.

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

[0061] Figure 4The machine shows the way of passing the obstacle section. For example, the turnout frog area, four groups of driving wheels are installed on the front and rear sides of the vehicle body, and the position of the outer side wheels and flanges is changed through the lifting device. Image sensors are installed on the front and rear rows of the vehicle to detect whether the turnout frog area is entered. Distance sensors are installed on the four driving wheel shafts to detect whether the wheel group passes through the frog area. When entering the turnout frog area, the control system controls the whole machine to slow down and stop, then lifts the outer side wheels and flanges of the first wheel group, and the inner side wheels and flanges are driven according to the second, third and fourth wheel fixing devices to drive the whole machine to run. After one wheel group passes through the frog area, the control system resets the outer side support wheels and flanges according to the distance sensor data until the whole machine passes through.

[0062] The content of the present application is not limited to the examples listed, and any equivalent transformation of the technical solutions of the present application made by a person of ordinary skill in the art by reading the specification of the present application is covered by the claims of the present application.

Claims

1. A collaborative flaw detection method for railway tracks based on dual mobile robots, characterized in that: The equipment used in the collaborative flaw detection method includes a dual-mobile robot track flaw detection device, a data processing and analysis terminal, and a main control system; the dual mobile robots are responsible for collaboratively performing flaw detection operations on the railway track. The main control system is used to plan and control the collaborative operation of the two robots in a unified manner; it is responsible for transmitting the flaw detection data of the two robots 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 to identify defects on the railway track; The dual-mobile robot track flaw detection equipment includes a shell, motor, drive wheels, detection equipment, and main control system; the detection equipment includes a track surface damage detection device and a track geometry parameter detection device. The track surface damage detection device is arranged at the bottom of the whole machine and close to the track surface. The track geometry parameter detection device requires the two robots to work together and needs to be installed on the whole machine in the direction of the track centerline. Includes the following steps: Step 1: Initialization and Preparation; Step 2: Start both robots and move them according to the synchronous control method; 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, they use a magnetic particle testing device to apply magnetic powder to the railway track. The magnetic field causes the magnetic powder to accumulate at the defect, thereby identifying the location and shape of the defect. Finally, they use eddy current testing sensors to scan the railway track and determine whether there are other types of defects on the track by detecting changes in eddy currents. The dual robots collect flaw detection data in real time and transmit it to the main control system for further processing and analysis; the collected flaw detection data is also transmitted to the data processing and analysis system for further processing and analysis. In step three, the dual-mobile robot track flaw detection equipment receives the first and second instructions from the data processing and analysis terminal through the main control system; In response to a first command, the dual-mobile robot track flaw detection equipment 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; in response to a second command, the dual-mobile robot track flaw detection equipment controls the track flaw detection equipment to acquire a first image during the sliding process on the track, the first image including image information of the track surface and the vicinity of the track. The track flaw detection equipment collects information and uploads it to the data processing and analysis terminal through the main control system, so that maintenance personnel can understand the entire flaw detection operation process and analyze and trace the damage to the track. Based on the first image, the damage to the track, track geometry parameters, and the surrounding environment of the line are analyzed.

2. The railway track collaborative flaw detection method based on dual mobile robots according to claim 1, characterized in that: The data processing and analysis terminal merges the flaw detection data from the two robots to improve the integrity and accuracy of the data; Defect identification: Algorithms and models are used to process and analyze the merged data to identify defects on the railway track; Result display: The identification results are displayed to users in the form of graphs and reports to facilitate user understanding and decision-making.

3. The railway track collaborative flaw detection method based on dual mobile robots according to claim 2, characterized in that: In step three, the main control system includes a control system, communication equipment, and positioning equipment. The communication equipment receives first and second instructions transmitted by the user to the main control system through a digital processing and analysis terminal, and sends them to the control system. In response to the first instruction, the positioning equipment obtains the initial position of the track flaw detection equipment and sends it to the control module. Based on the first spacing and the initial position, the control module controls the sliding module to move the track flaw detection equipment on the track. Simultaneously, in response to the second instruction, the control module controls the vision sensor to acquire a first image during the sliding of the track flaw detection equipment on the track. This first image includes image information of the track and the tunnel where the track is located. Based on the first image, the control module analyzes the damage condition of the track.

4. The railway track collaborative flaw detection method based on dual mobile robots according to claim 3, characterized in that: In step three, the control system includes a synchronization control subsystem and a collision avoidance subsystem. The synchronization control strategy is used to ensure that the two robots maintain a high degree of consistency during walking and flaw detection. The specific synchronization control method is as follows: Time synchronization: Ensure that the two robots perform the same operation at the same time point through timestamps or time synchronization protocols; Position synchronization: Ensure that the two robots perform flaw detection operations at the same location by monitoring their position information in real time; Speed ​​synchronization: Ensure that the two robots travel the same distance within the same time period by adjusting their walking speed.

5. A collaborative flaw detection method for railway tracks based on dual mobile robots according to claim 4, characterized in that: In step three, 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 method is as follows: Sensor-based collision detection: Sensors are installed to monitor the relative position and attitude between the two robots in real time. Once a potential collision risk is detected, corresponding measures are taken immediately to avoid it. Vision-based collision detection: Visual sensors are used to monitor the surrounding environment of the two robots in real time, and image processing algorithms are used to identify potential collision risks.

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