Multi-vehicle-type adaptive identification and intelligent disassembly equipment and method

Abstract

The invention discloses multi-vehicle-type self-adaptive identification and intelligent disassembly equipment and method.The equipment comprises a mobile device and a mechanical arm, the mobile device is arranged close to a rail and can move in the rail direction, a 3D visual system is arranged on the mobile device and used for scanning the end wall and the side wall of a railway wagon, the fixed end of the mechanical arm is connected with the mobile device, and the fixed end of the mechanical arm is connected with the mobile device; the multi-vehicle-type self-adaptive recognition and intelligent disintegration equipment coordinates actions of the 3D visual system, the thickness detection system, the laser ranging system and the cutting equipment through the control system, and the multi-vehicle-type self-adaptive recognition and intelligent disintegration equipment has the advantages that the 3D visual system, the thickness detection system, the laser ranging system and the cutting equipment are controlled by the control system, so that the multi-vehicle-type self-adaptive recognition and intelligent disintegration equipment is more intelligent; and generating a first cutting track based on a scanning result of the 3D visual system by using the intelligent module. The thickness detection system and the laser ranging system are used for optimizing the first cutting track and supplementing cutting parameters, so that the situation that cutting equipment does not cut thoroughly or collides when moving along the first cutting track is avoided.

Description

Technical Field

[0001] This invention belongs to the technical field of railway freight car cutting equipment, and more specifically, relates to a multi-model adaptive recognition and intelligent dismantling device and method. Background Technology

[0002] During railway freight car repairs, damaged or corroded sections of the endwalls need to be replaced. Traditional cutting methods rely on manual operation, which is inefficient and makes it difficult to guarantee cutting accuracy. Especially when the freight cars are parked on the tracks, manual cutting is not only cumbersome but also requires a large space and high labor costs.

[0003] While some automated cutting equipment exists in the current technology, most rely on fixed cutting trajectories or require manual adjustments, failing to flexibly adapt to different types and degrees of damage to the endwalls of freight cars. Furthermore, the different manufacturers and repair shops of railway freight cars result in significant dimensional errors between them. This makes mechanical positioning methods unsuitable for actual cutting needs. Therefore, there is an urgent need for equipment capable of automatically positioning and cutting based on the actual dimensions and damage condition of the freight car endwalls. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by providing a multi-vehicle adaptive recognition and intelligent disassembly device, which solves the problem that existing devices cannot flexibly adapt to the end walls of trucks of different models or degrees of damage.

[0005] To achieve the above objectives, the present invention provides a multi-vehicle adaptive recognition and intelligent disassembly device, comprising: A mobile device is positioned close to the railway track and is capable of moving along the track. The mobile device is equipped with a 3D vision system for scanning the end walls and side walls of railway freight cars. A robotic arm, the fixed end of which is connected to the mobile device, and the mobile end of which is equipped with a cutting device and a feedback system, the feedback system including a thickness detection system and a laser ranging system; The control system is electrically connected to the 3D vision system, the thickness detection system, the laser ranging system, and the cutting equipment.

[0006] Optionally, the mobile device includes: At least one track is provided, which is parallel to the railway rails. At least one mobile trolley is provided on the track. The 3D vision system is provided on the mobile trolley via a connecting arm. The fixed end of the robotic arm is provided on the mobile trolley.

[0007] Optionally, the connecting arm is further provided with a protective mechanism for protecting the 3D vision system.

[0008] Optionally, the connecting arm is located on the side of the robotic arm away from the rail.

[0009] Optionally, the laser ranging system is used to detect whether the end face has deformed or has an obstacle.

[0010] This invention also provides a multi-vehicle adaptive recognition and intelligent disassembly method, utilizing the aforementioned multi-vehicle adaptive recognition and intelligent disassembly device, comprising: The truck body structure is obtained by scanning with a 3D vision system, and image information of the area to be cut is generated. Based on the image information of the area to be cut, the damaged area is determined, and the first cutting trajectory is generated; The robotic arm drives the thickness detection system and the laser ranging system to move along the first cutting trajectory, and corrects the first cutting trajectory to the second cutting trajectory. The robotic arm drives the cutting equipment to cut along the second cutting trajectory.

[0011] Optionally, it also includes: If the thickness detection system detects a change in thickness in a certain area on the first cutting trajectory, it adjusts the cutting parameters for that area.

[0012] Optionally, adjusting the cutting parameters of the corresponding area includes adjusting the cutting power and / or adjusting the cutting movement speed.

[0013] Optionally, if the laser ranging system detects deformation in a certain area on the first cutting trajectory, the path of the first cutting trajectory is adjusted.

[0014] Optionally, the path for adjusting the first cutting trajectory may include avoiding the deformation area or issuing an alarm.

[0015] This invention provides a multi-vehicle adaptive recognition and intelligent disassembly device, the advantages of which are: The multi-vehicle adaptive recognition and intelligent disassembly equipment control system coordinates the actions of the 3D vision system, thickness detection system, laser ranging system, and cutting equipment. It utilizes an intelligent module to generate a first cutting trajectory based on the scanning results of the 3D vision system. The thickness detection system and laser ranging system optimize the first cutting trajectory and supplement cutting parameters to prevent incomplete cutting or collisions when the cutting equipment moves along the first cutting trajectory.

[0016] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0017] The above and other objects, features and advantages of the present invention will become more apparent from the more detailed description of exemplary embodiments of the invention in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the invention.

[0018] Fig. 1 A schematic diagram of a multi-vehicle adaptive recognition and intelligent disassembly device according to an embodiment of the present invention is shown.

[0019] Fig. 2 A side view of a mobile device for a multi-model adaptive recognition and intelligent disassembly device according to an embodiment of the present invention is shown.

[0020] Fig. 3 A front view of a mobile device for a multi-model adaptive recognition and intelligent disassembly device according to an embodiment of the present invention is shown.

[0021] Explanation of reference numerals in the attached figures: 1. Railway tracks; 2. Mobile equipment; 3. 3D vision system; 4. Feedback system; 5. Robotic arm; 6. Cutting equipment; 7. Protective mechanism. Detailed Implementation

[0022] Preferred embodiments of the invention will now be described in more detail. While preferred embodiments of the invention are described below, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0023] like Figs. 1-3 As shown, a multi-vehicle adaptive recognition and intelligent disassembly device includes: Mobile device 2 is positioned close to rail 1 and can move along the direction of rail 1. Mobile device 2 is equipped with a 3D vision system 3, which is used to scan the end walls and side walls of railway freight cars. The robotic arm 5 has a fixed end connected to the mobile device 2. The mobile end of the robotic arm 5 is equipped with a cutting device 6 and a feedback system 4. The feedback system 4 includes a thickness detection system and a laser rangefinder system. The control system is electrically connected to the 3D vision system 3, the thickness detection system, the laser rangefinder system, and the cutting equipment 6.

[0024] Specifically, the control system includes an intelligent module. The control system coordinates the actions of the 3D vision system 3, the thickness detection system, the laser ranging system, and the cutting device 6, and uses the intelligent module to generate a first cutting trajectory based on the scanning results of the 3D vision system 3. The thickness detection system and the laser ranging system are used to optimize the first cutting trajectory and supplement the cutting parameters to avoid incomplete cutting or collisions when the cutting device 6 moves along the first cutting trajectory.

[0025] Furthermore, the 3D vision system 3 includes a housing, which is rectangular in shape, with a projector and a high-resolution camera respectively installed at both ends near the rails. The housing also has a heat dissipation structure.

[0026] In use, the mobile device 2 first moves the robotic arm 5 and the 3D vision system 3 on the gantry, enabling the 3D vision system 3 to scan the entire end wall. Then, based on the scanning results of the 3D vision system 3, a first cutting trajectory is generated. The robotic arm 5 then uses the thickness detection system and the laser ranging system to check the first cutting trajectory and correct it to generate a second cutting trajectory. Finally, the robotic arm 5 moves the cutting device 6 along the second cutting trajectory, while the laser ranging system moves with the cutting device 6. The control system adjusts the distance between the cutting head and the end face according to the detection results.

[0027] Furthermore, the first cutting trajectory is merely a contour trajectory around the area to be cut, while the second cutting trajectory, based on the optimized contour trajectory, adds settings for cutting parameters to ensure cutting quality. A laser ranging system improves the accuracy of the generated cutting path, preventing damage to the cutting equipment 6 due to undetected deformation. A thickness detection system optimizes the cutting trajectory and adjusts cutting parameters based on the actual thickness and deformation of the truck end wall, ensuring cutting quality.

[0028] Furthermore, the cutting device 6 is a plasma cutting gun, and a monitoring probe is installed on the robotic arm 5 or the mobile device 2 to continuously monitor the condition of the cutting area. The software environment for the device is C++11.0, OpenCV, Qt, and Eigen. The hardware environment includes an industrial computer CPU of i9-13900K and an industrial computer GPU of RTX4080; an industrial robotic arm, a binocular structured light camera, a point laser rangefinder, and the plasma cutting equipment is developed in C++.

[0029] In this embodiment, the mobile device 2 includes: At least one track is provided, parallel to rail 1, and at least one mobile trolley is provided on the track. A 3D vision system 3 is provided on the mobile trolley via a connecting arm, and the fixed end of the robotic arm is provided on the mobile trolley.

[0030] Specifically, tracks are installed on at least one side of the vehicle body, and multiple tracks can be installed in parallel. A trolley moves along the tracks, driving the cutting equipment to adapt to use on the vehicle's side walls.

[0031] Furthermore, the control system is integrated onto the mobile trolley, which is equipped with a power module and a temperature control module. The robotic arm 5 is equipped with a calibration needle. A gantry can also be erected on the rails, allowing the mobile trolley to be movably mounted onto it for use with end walls.

[0032] In this embodiment, a protective mechanism 7 is also provided on the connecting arm, which is used to protect the 3D vision system 3.

[0033] Specifically, the protective mechanism 7 is a protective shell through which the 3D vision system 3 is protected after use. At least one of the protective mechanism 7 and the 3D vision system 3 is movable. Preferably, the 3D vision system 3 is movably mounted on the connecting arm, facilitating the movement of the 3D vision system 3 to scan the vehicle body. After scanning, the 3D vision system 3 enters the protective mechanism 7.

[0034] In this embodiment, the connecting arm is located on the side of the robotic arm 5 away from the rail 1.

[0035] Specifically, to avoid damaging the 3D vision system 3 during cutting, the 3D vision system 3 or a camera added to the connecting arm is used to monitor the cutting process.

[0036] In this embodiment, the laser ranging system is used to detect whether the end face has deformed or has an obstacle.

[0037] Specifically, the laser ranging system optimizes the first cutting trajectory, supplements the details of the 3D vision system 3, and avoids collisions during cutting, ensuring stable cutting.

[0038] This invention also provides a multi-vehicle adaptive recognition and intelligent disassembly method, utilizing the aforementioned multi-vehicle adaptive recognition and intelligent disassembly device, comprising: The truck body structure is obtained by scanning using a 3D vision system, and image information of the area to be cut is generated. Based on the image information of the area to be cut, the damaged area is determined, and the first cutting trajectory is generated; The robotic arm 5 drives the thickness detection system and the laser ranging system to move along the first cutting trajectory, and corrects the first cutting trajectory to the second cutting trajectory. The robotic arm 5 drives the cutting device 6 to cut along the second cutting trajectory.

[0039] Specifically, The truck body structure is obtained by scanning using a 3D vision system, and image information of the area to be cut is generated. Based on the image information of the area to be cut, the damaged area is determined, and a first cutting trajectory is generated around the damaged area. The first cutting trajectory is only the initial movement path of the cutting device 6. The robotic arm 5 drives the thickness detection system and the laser ranging system to move along the first cutting trajectory, corrects the first cutting trajectory to the second cutting trajectory, modifies the initial movement path according to the thickness and shape changes of the end face on the initial movement path, and sets the cutting parameters, including cutting power, moving speed, etc., thereby optimizing the first cutting trajectory and ensuring the accuracy of the cutting path generation. The robotic arm 5 drives the cutting device 6 to cut along the second cutting trajectory. At the same time, the laser ranging system monitors the gap between the cutting device 6 and the end face, which facilitates the adjustment of the parameters of the cutting device 6 and avoids collisions.

[0040] In this embodiment, it also includes: If the thickness detection system detects a change in thickness in a certain area on the first cutting trajectory, it adjusts the cutting parameters for that area.

[0041] Specifically, the cutting parameters are adjusted according to the thickness variation to ensure the cutting effect.

[0042] In this embodiment, adjusting the cutting parameters of the corresponding area includes adjusting the cutting power and / or adjusting the cutting movement speed.

[0043] In this embodiment, if the laser ranging system detects deformation in a certain area on the first cutting trajectory, the path of the first cutting trajectory is adjusted.

[0044] Specifically, the laser ranging system avoids collisions with the cutting device 6, and at the same time, the laser ranging system can make precise adjustments to details that the 3D vision system 3 fails to notice.

[0045] In this embodiment, adjusting the path of the first cutting trajectory includes avoiding the deformation area or issuing an alarm.

[0046] Specifically, if excessive deformation in certain areas causes significant changes in the first cutting trajectory, an alarm will be triggered for manual intervention.

[0047] This embodiment demonstrates the use of a multi-model adaptive recognition and intelligent disassembly device, taking the end face cutting of a railway freight car as an example: The railway freight car stopped close to the tracks; Mobile device 2, mobile 3D vision system 3, scans the end face of railway freight cars; The truck body structure is obtained by scanning using a 3D vision system, and image information of the area to be cut is generated. Based on the image information of the area to be cut, the damaged area is determined, and a first cutting trajectory around the damaged area is generated. The first cutting trajectory is only the initial movement path of the cutting device 6. At the same time, the 3D vision system 3 is protected by a protective shell. The robotic arm 5 drives the thickness detection system and the laser ranging system to move along the first cutting trajectory, corrects the first cutting trajectory to the second cutting trajectory, modifies the initial movement path according to the thickness and shape changes of the end face on the initial movement path, and sets the cutting parameters, including cutting power, moving speed, etc., thereby optimizing the first cutting trajectory and ensuring the accuracy of the cutting path generation. If the end face deforms or the thickness increases significantly, an alarm will be issued and manual handling will be required. The robotic arm 5 drives the cutting device 6 to cut along the second cutting trajectory. At the same time, the laser ranging system monitors the gap between the cutting device 6 and the end face, which facilitates the adjustment of the parameters of the cutting device 6 and avoids collisions. After the cutting was completed, the railway freight cars drove away.

[0048] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A multi-vehicle adaptive recognition and intelligent disassembly device, characterized in that, include: A mobile device is positioned close to the railway track and is capable of moving along the track. The mobile device is equipped with a 3D vision system for scanning the end walls and side walls of railway freight cars. A robotic arm, the fixed end of which is connected to the mobile device, and the mobile end of which is equipped with a cutting device and a feedback system, the feedback system including a thickness detection system and a laser ranging system; The control system is electrically connected to the 3D vision system, the thickness detection system, the laser ranging system, and the cutting equipment.

2. The multi-vehicle adaptive recognition and intelligent disassembly device according to claim 1, characterized in that, The mobile device includes: At least one track is provided, which is parallel to the railway rails. At least one mobile trolley is provided on the track. The 3D vision system is provided on the mobile trolley via a connecting arm. The fixed end of the robotic arm is provided on the mobile trolley.

3. The multi-vehicle adaptive recognition and intelligent disassembly device according to claim 2, characterized in that, The connecting arm is also equipped with a protective mechanism, which is used to protect the 3D vision system.

4. The multi-vehicle adaptive recognition and intelligent disassembly device according to claim 2, characterized in that, The connecting arm is located on the side of the robotic arm away from the rails.

5. The multi-vehicle adaptive recognition and intelligent disassembly device according to claim 1, characterized in that, The laser ranging system is used to detect whether the end face has deformed or has obstacles.

6. A multi-vehicle adaptive recognition and intelligent disassembly method, utilizing the multi-vehicle adaptive recognition and intelligent disassembly device according to any one of claims 1-5, characterized in that, include: The truck body structure is obtained by scanning with a 3D vision system, and image information of the area to be cut is generated. Based on the image information of the area to be cut, the damaged area is determined, and the first cutting trajectory is generated; The robotic arm drives the thickness detection system and the laser ranging system to move along the first cutting trajectory, and corrects the first cutting trajectory to the second cutting trajectory. The robotic arm drives the cutting equipment to cut along the second cutting trajectory.

7. The multi-vehicle adaptive recognition and intelligent disassembly method according to claim 6, characterized in that, Also includes: If the thickness detection system detects a change in thickness in a certain area on the first cutting trajectory, it adjusts the cutting parameters for that area.

8. The multi-vehicle adaptive recognition and intelligent disassembly method according to claim 7, characterized in that, The adjustment of the cutting parameters for the corresponding area includes adjusting the cutting power and / or adjusting the cutting movement speed.

9. The multi-vehicle adaptive recognition and intelligent disassembly method according to claim 6, characterized in that, If the laser ranging system detects deformation in a certain area on the first cutting trajectory, the path of the first cutting trajectory will be adjusted.

10. The multi-vehicle adaptive recognition and intelligent disassembly method according to claim 6, characterized in that, The path for adjusting the first cutting trajectory includes avoiding the deformation area or issuing an alarm.

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