Automatic oil chromatography maintenance system and method based on mobile robot

Abstract

The invention relates to the technical field of oil chromatography automatic maintenance, and provides an oil chromatography automatic maintenance system and method based on a mobile robot, and the system comprises the mobile robot which comprises a mobile chassis, a robot body, a visual module and a laser radar; the robot body, the visual module and the laser radar are all arranged on the movable chassis; the central control machine is arranged on the movable chassis and comprises a data processing module, a navigation sensing module and a controller module; the data processing module is electrically connected with the monitoring platform, the navigation sensing module is electrically connected with the visual module and the laser radar through the data processing module, and the controller module is electrically connected with the robot body and the visual module through the data processing module. The system can realize real-time analysis of oil chromatography data and accurate positioning of faults, so that the maintenance process is more efficient and accurate. The oil chromatogram automatic maintenance system avoids the requirement that workers work in dangerous environments such as high pressure and high temperature.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic maintenance of oil chromatography, and in particular, to an automatic maintenance system and method for oil chromatography based on a mobile robot. Background Art

[0002] In the power system, the safe and stable operation of large power equipment such as transformers is crucial for the power grid. Transformer oil, as an insulating and cooling medium, plays a key role in the normal operation of transformers. Oil chromatography analysis, as an effective means of monitoring internal faults of transformers, is of crucial significance for timely detecting potential insulation defects, overheating faults, etc.

[0003] In recent years, with the progress of robot technology and automation technology, methods of using fixed online monitoring devices for oil chromatography analysis have emerged. These online monitoring devices can collect and analyze oil chromatography data in real time and continuously, overcoming the problem of long sampling intervals in traditional manual sampling, making the monitoring of the operating state of power equipment more timely and accurate.

[0004] When the oil chromatography online detection device fails, the current countermeasures mainly rely on manual maintenance and repair. However, the oil chromatography online detection device is usually installed near power equipment, and there may be dangerous factors such as high voltage and high temperature. When maintenance personnel handle faults, they need to work in these dangerous environments. If the operation is improper or the protection measures are not in place, safety accidents such as electric shock and scalding are likely to occur. In addition, some faults may cause problems such as oil sample leakage. The oil sample may be somewhat toxic, and if maintenance personnel come into contact with the leaked oil sample during manual handling, it will cause harm to the physical health of the maintenance personnel. Summary of the Invention

[0005] The present invention provides an automatic maintenance system and method for oil chromatography based on a mobile robot to solve the problem that existing oil chromatography analysis requires manual handling, and working in these dangerous environments is likely to cause safety accidents such as electric shock and scalding if the operation is improper or the protection measures are not in place.

[0006] The present invention provides an automatic maintenance system for oil chromatography based on a mobile robot, which is applied to a device to be tested having a monitoring platform, and includes: A mobile robot, including: a mobile chassis, a robot body, a vision module, and a lidar; the robot body, the vision module, and the lidar are all arranged on the mobile chassis; The central control unit is arranged on the mobile chassis and includes a data processing module, a navigation perception module, and a controller module; the data processing module is electrically connected to the monitoring platform, the navigation perception module is electrically connected to the vision module and the lidar through the data processing module, and the controller module is electrically connected to the robot body and the vision module through the data processing module; The data processing module is used to obtain the oil chromatogram data of the device under test monitored by the monitoring platform, and when it detects that the oil chromatogram data is abnormal, it controls the navigation perception module to collect environmental information through the vision module and the lidar. Under the control of the navigation perception module, the mobile chassis is controlled to reach a specified position, and the controller module controls the robot body to repair the device under test under the guidance of the vision module.

[0007] According to an oil chromatogram automatic maintenance system based on a mobile robot provided by the present invention, the vision module includes: A 3D camera and a camera bracket. The 3D camera is connected to the mobile chassis through the camera bracket, and the 3D camera is electrically connected to the controller module through the data processing module; A plurality of 2D cameras are evenly arranged around the mobile chassis, and the 2D cameras are electrically connected to the navigation perception module through the data processing module.

[0008] According to an oil chromatogram automatic maintenance system based on a mobile robot provided by the present invention, the navigation perception module generates a dynamic navigation path for the mobile chassis by fusing the obstacle detection data of the lidar and the 360° environmental images of the plurality of 2D cameras.

[0009] According to an oil chromatogram automatic maintenance system based on a mobile robot provided by the present invention, the robot body includes: A robotic arm and a robot hand. One end of the robotic arm is connected to the robot hand, and the other end of the robotic arm is connected to the mobile chassis. Both the robotic arm and the robot hand are electrically connected to the controller module.

[0010] According to an oil chromatogram automatic maintenance system based on a mobile robot provided by the present invention, the central control unit further includes: A pattern recognition module is electrically connected to the vision module through the data processing module, and is used to locate the oil leakage point of the device under test and identify the fault type.

[0011] According to an oil chromatogram automatic maintenance system based on a mobile robot provided by the present invention, the central control unit further includes: A communication module, electrically connected to the data processing module, the navigation and perception module, and the controller module, for communicating with the monitoring platform, the mobile chassis, the robot body, the vision module, and the lidar.

[0012] The present invention also provides a method for overhauling an oil chromatograph automatic overhaul system based on the above mobile robot, comprising the following steps: The monitoring platform collects the oil chromatograph data of the device to be measured in real time and transmits it to the central control unit; The data processing module performs threshold analysis on the oil chromatograph data. If data anomalies are detected, it triggers the navigation and perception module to collect the first environmental information through the vision module and the lidar; The navigation and perception module generates a first dynamic navigation path based on the first environmental information and controls the mobile chassis to move to a specified position of the monitoring platform; The controller module controls the robot body to perform maintenance operations on the device to be measured under the guidance of the vision module.

[0013] According to the method provided by the present invention, the step of the controller module controlling the robot body to perform maintenance operations on the device to be measured under the guidance of the vision module includes: Locate the oil leakage point of the device to be measured through a three-dimensional camera, and determine the fault type by the pattern recognition module; The controller module controls the manipulator and the mechanical hand to perform maintenance operations according to the fault type.

[0014] According to the method provided by the present invention, it further includes: After the maintenance is completed, monitor the repair status through a three-dimensional camera and / or the monitoring platform; If it is detected that the data has recovered and there is no oil leakage, trigger the navigation and perception module to collect the second environmental information through the vision module and the lidar; The navigation and perception module generates a second dynamic navigation path based on the second environmental information and controls the mobile chassis to return to the initial position.

[0015] According to the method provided by the present invention, it further includes: If it is detected that the data has not recovered or there is an oil leakage, an alarm is issued.

[0016] The oil chromatograph automatic maintenance system and method based on a mobile robot provided by the present invention integrate advanced modules such as data processing, communication, navigation perception, and pattern recognition, and can achieve real-time analysis of oil chromatograph data and accurate positioning of faults, making the maintenance process more efficient and accurate. The mobile robot can quickly respond to abnormal situations and execute maintenance actions with high precision. By automatically completing oil chromatograph detection and maintenance tasks, the oil chromatograph automatic maintenance system avoids the need for manual work in dangerous environments such as high voltage and high temperature, and greatly reduces the risk of safety accidents such as electric shock and scalding. In addition, for possible oil sample leakage problems, mobile robot operation can effectively prevent maintenance personnel from directly contacting toxic substances and protect the health and safety of the staff. The oil chromatograph automatic maintenance system provided by the present invention not only solves the safety hazards in the prior art, but also greatly improves the efficiency and accuracy of maintenance work, which is an important progress in the intelligent operation and maintenance of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 is a schematic diagram of the oil chromatograph automatic maintenance system based on a mobile robot provided by an embodiment of the present invention.

[0019] Figure 2 is a schematic diagram of the central control machine provided by an embodiment of the present invention.

[0020] Figure 3 is one of the schematic flowcharts of the method for maintaining the oil chromatograph automatic maintenance system based on a mobile robot provided by an embodiment of the present invention.

[0021] Figure 4 is the second of the schematic flowcharts of the method for maintaining the oil chromatograph automatic maintenance system based on a mobile robot provided by an embodiment of the present invention.

[0022] REFERENCE SIGNS: 1, mobile chassis; 2, robotic arm; 3, mechanical hand; 4, 3D camera; 5, camera support; 6, first camera; 7, second camera; 8, third camera; 9, fourth camera; 10, lidar; 11, central control machine; 12, data processing module; 13, navigation perception module; 14, controller module; 15, pattern recognition module; 16, communication module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] To make the objectives, technical solutions and advantages of the present invention more clear, the following will clearly and completely describe the technical solutions in the present invention in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without making creative efforts fall within the protection scope of the present invention.

[0024] The following will describe Figures 1 - 4 the oil chromatogram automatic maintenance system and method based on a mobile robot of the present invention.

[0025] The present invention provides an oil chromatogram automatic maintenance system based on a mobile robot, as Figure 1 and Figure 2 shown. The mobile robot includes: a mobile chassis 1, a robot body, a vision module and a lidar 10; the robot body, the vision module and the lidar 10 are all arranged on the mobile chassis 1. A central control machine 11 is arranged on the mobile chassis 1, and includes a data processing module 12, a navigation perception module 13 and a controller module 14; the data processing module 12 is electrically connected to the monitoring platform, the navigation perception module 13 is electrically connected to the vision module and the lidar 10 through the data processing module 12, and the controller module 14 is electrically connected to the robot body and the vision module through the data processing module 12; the data processing module 12 is used to obtain the oil chromatogram data of the device under test monitored by the monitoring platform, and when detecting abnormal oil chromatogram data, control the navigation perception module 13 to collect environmental information through the vision module and the lidar 10, and under the control of the navigation perception module 13, control the mobile chassis 1 to reach the designated position, and the controller module 14 controls the robot body to repair the device under test under the guidance of the vision module.

[0026] In this embodiment, the mobile chassis 1 is responsible for carrying and driving the robot body to the designated position. The robot body performs specific maintenance tasks, such as replacing components, adjusting settings, etc.

[0027] The vision module provides high-resolution images and video information for environmental perception and target recognition to assist the robot in precise operation. The lidar 10 measures distances by emitting lasers and receiving reflected signals to construct a three-dimensional map of the environment for precise navigation and obstacle avoidance.

[0028] The data processing module 12 is responsible for receiving the oil chromatogram data sent by the monitoring platform, analyzing the data and judging whether there is any abnormality. The navigation perception module 13 calls the vision module and the lidar 10 to collect environmental information according to the judgment of the data processing module 12 and plan the moving path. The controller module 14 receives the instructions of the navigation perception module 13, controls the movement of the mobile chassis 1, and coordinates the robot body and the vision module to complete the maintenance task.

[0029] During operation, the oil chromatographic data of the device under test is collected in real time through the monitoring platform and transmitted to the central control unit 11; the data processing module 12 performs threshold analysis on the oil chromatographic data. If abnormal data is detected, the navigation perception module 13 is triggered to collect the first environmental information through the vision module and the lidar 10 (triggering the maintenance process). The navigation perception module 13 generates a first dynamic navigation path based on the first environmental information and controls the mobile chassis 1 to move to a specified position on the monitoring platform; the controller module 14 controls the robot body to perform maintenance operations on the device under test under the guidance of the vision module, such as replacing components, adjusting parameters, etc.

[0030] The automatic oil chromatographic maintenance system based on a mobile robot provided by the present invention integrates advanced modules such as data processing, communication, navigation perception, and pattern recognition, and can realize real-time analysis of oil chromatographic data and accurate positioning of faults, making the maintenance process more efficient and accurate. The mobile robot can quickly respond to abnormal situations and perform maintenance actions with high precision. By automatically completing the oil chromatographic detection and maintenance tasks, the automatic oil chromatographic maintenance system avoids the need for manual work in dangerous environments such as high voltage and high temperature, and greatly reduces the risk of safety accidents such as electric shock and scalding. In addition, for possible oil sample leakage problems, the operation of the mobile robot can effectively prevent maintenance personnel from directly contacting toxic substances, protecting the health and safety of the staff. The automatic oil chromatographic maintenance system provided by the present invention not only solves the safety hazards in the prior art, but also greatly improves the efficiency and accuracy of the maintenance work, which is an important progress in the intelligent operation and maintenance of the power system.

[0031] In some embodiments, as Figure 1 and Figure 2 shown, the vision module includes: a plurality of two-dimensional cameras, a three-dimensional camera 4, and a camera bracket 5. The three-dimensional camera 4 is connected to the mobile chassis 1 through the camera bracket 5, and the three-dimensional camera 4 is electrically connected to the controller module 14 through the data processing module 12; a plurality of two-dimensional cameras are evenly arranged around the mobile chassis 1, and the two-dimensional cameras are electrically connected to the navigation perception module 13 through the data processing module 12.

[0032] Specifically, the 3D camera 4 can capture the 3D information of the environment and generate high-precision 3D maps or point cloud data. The 3D camera 4 is firmly connected to the mobile chassis 1 through the camera bracket 5 and is electrically connected to the controller module 14 through the data processing module 12. In this way, the controller module 14 can obtain the 3D information of the environment in real time for path planning and obstacle avoidance decision-making, and at the same time for facilitating subsequent maintenance operations. A plurality of 2D cameras are evenly arranged around the mobile chassis 1, providing an all-round field of view. This helps to capture more environmental details and improve the comprehensiveness and accuracy of environmental perception. The 2D cameras are electrically connected to the navigation perception module 13 through the data processing module 12. The navigation perception module 13 can use this 2D image information for operations such as target recognition, obstacle detection, and path optimization.

[0033] Generally, there are four 2D cameras, namely the first camera 6, the second camera 7, the third camera 8, and the fourth camera 9, which are respectively arranged in the front, back, left, and right of the mobile chassis 1. The first camera 6 (front camera) is usually installed at the front end of the mobile chassis 1 and is mainly used to capture the environmental information in the front, helping the system to identify obstacles, road signs, pedestrians, etc. in the front to support the forward navigation and obstacle avoidance functions. The second camera 7 (rear camera) is installed at the rear end of the mobile chassis 1 and is mainly used to monitor the environment in the rear to ensure that obstacles can be detected and avoided in time when reversing or backing up. The third camera 8 (left camera) is installed on the left side of the mobile chassis 1 and is responsible for capturing the environmental information on the left. The fourth camera 9 (right camera) is installed on the right side of the mobile chassis 1 and is similar to the left camera but focuses on capturing the environmental information on the right.

[0034] By using these four cameras in combination, the mobile chassis 1 can achieve all-round monitoring of the surrounding environment, thereby improving the accuracy and reliability of its navigation, positioning, and obstacle avoidance.

[0035] In this embodiment, by combining the information of the 2D cameras and the 3D camera 4, the system can perceive the environment more comprehensively and improve its adaptability to environmental changes.

[0036] The navigation perception module 13 generates a dynamic navigation path for the mobile chassis 1 by fusing the obstacle detection data of the lidar 10 and the 360° environmental images of multiple 2D cameras.

[0037] Among them, the lidar 10 measures distances by emitting laser beams and receiving reflected signals, thereby constructing an accurate three-dimensional map of the surrounding environment. Multiple two-dimensional cameras are evenly distributed around the mobile chassis 1, providing an all-round field of view. The images captured by these cameras contain rich environmental details such as textures, colors, and shapes, which help to identify obstacles, road signs, and other important features. The navigation perception module 13 fuses the obstacle detection data of the lidar 10 and the image data of the two-dimensional cameras. By fusing the data of the lidar 10 and the two-dimensional cameras, the navigation perception module 13 can more accurately perceive the environment, thereby improving the accuracy and reliability of navigation.

[0038] In some embodiments, such as Figure 1 and Figure 2 shown, the robot body includes: a robotic arm 2 and a robotic hand 3. One end of the robotic arm 2 is connected to the robotic hand 3, and the other end of the robotic arm 2 is connected to the mobile chassis 1. Both the robotic arm 2 and the robotic hand 3 are electrically connected to the controller module 14.

[0039] In this embodiment, the robotic arm 2 is responsible for moving and positioning the robotic hand 3 in three-dimensional space to achieve precise operation of the target device. The robotic arm 2 usually has multiple joints and can move flexibly in multiple directions. The robotic arm 2 is electrically connected to the controller module 14, receives instructions from the controller module 14, and controls the movement trajectory and speed of the robotic arm 2. The robotic hand 3 is a tool for performing specific maintenance tasks, such as replacing components, adjusting settings, or performing other fine operations. The robotic hand 3 is connected to one end of the robotic arm 2 and achieves precise operation of the target device through the movement and positioning of the robotic arm 2. The robotic hand 3 is also electrically connected to the controller module 14, receives instructions from the controller module 14, and controls the grasping, releasing, or other actions of the robotic hand 3.

[0040] In some embodiments, such as Figure 2 shown, the central control unit 11 further includes: a pattern recognition module 15. The pattern recognition module 15 is electrically connected to the vision module through the data processing module 12 and is used to locate the oil leakage point of the device to be tested and identify the fault type.

[0041] In this embodiment, the pattern recognition module 15 uses image processing algorithms to deeply analyze the processed data. It can identify abnormal areas in the image, such as oil stains and oil droplets, so as to accurately locate the oil leakage point of the device to be tested. On the basis of locating the oil leakage point, the pattern recognition module 15 can further analyze the characteristics of the oil leakage point, such as the oil leakage speed, oil leakage color, and oil leakage position, so as to identify the specific fault type. For example, it may be able to distinguish whether it is due to seal aging, pipeline.

[0042] In some embodiments, such as Figure 2As shown in the figure, the central control unit 11 further includes: a communication module 16. The communication module 16 is electrically connected to the data processing module 12, the navigation perception module 13, and the controller module 14 for communicating with the monitoring platform, the mobile chassis 1, the robot body, the vision module, and the lidar 10.

[0043] In this embodiment, the communication module 16 is not only connected to the internal modules of the central control unit 11, but also establishes communication connections with external components such as the monitoring platform, the mobile chassis 1, the robot body, the vision module, and the lidar 10. This extensive communication capability enables the central control unit 11 to acquire and process data from various components in real time and send control instructions to them simultaneously.

[0044] In the communication with the monitoring platform, the communication module 16 is responsible for uploading the collected data to the platform for analysis and storage, and at the same time receiving the control strategies and task instructions issued by the platform. In the communication with the mobile chassis 1 and the robot body, the communication module 16 sends navigation instructions, operation instructions, and status query requests to ensure that they can execute tasks according to the predetermined path and maintain the best working state.

[0045] The embodiment of the present invention also provides a method for overhauling an oil chromatograph automatic overhaul system based on a mobile robot. As Figure 3 shown, the specific structure of the oil chromatograph automatic overhaul system can be referred to Figure 1 and Figure 2 the relevant written description. The method for overhauling the oil chromatograph automatic overhaul system includes the following steps: Step S310: Real-time collect the oil chromatograph data of the device to be tested through the monitoring platform and transmit it to the central control unit.

[0046] Step S320: The data processing module performs threshold analysis on the oil chromatograph data. If data anomalies are detected, trigger the navigation perception module to collect the first environmental information through the vision module and the lidar.

[0047] Step S330: The navigation perception module generates a first dynamic navigation path based on the first environmental information and controls the mobile chassis to move to the designated position of the monitoring platform.

[0048] Step S340: The controller module controls the robot body to perform maintenance operations on the device to be tested under the guidance of the vision module.

[0049] During the working process, the oil chromatograph data of the device to be tested is collected in real time through the monitoring platform. The oil chromatograph data can reflect the oil quality status inside the device, including possible fault information. The collected data is immediately transmitted to the central control unit for subsequent processing and analysis.

[0050] The data processing module performs threshold analysis on the received oil chromatographic data. If the data exceeds the preset normal range, it is determined that the data is abnormal. Once data abnormality is detected, the system triggers the navigation perception module. The navigation perception module then collects the first environmental information through the vision module and lidar, including the spatial layout around the equipment, the positions of obstacles, etc. If the data does not exceed the preset normal range, the oil chromatographic data of the device under test is continuously collected in real time through the monitoring platform.

[0051] Based on the collected first environmental information, the navigation perception module generates a first dynamic navigation path. The first dynamic navigation path is designed to guide the mobile chassis to move safely and efficiently to the designated position of the monitoring platform. The controller module controls the mobile chassis to move along a predetermined trajectory according to the generated navigation path.

[0052] Under the guidance of the vision module, the robot body can accurately identify and locate the device under test. The controller module further controls the robot body to perform specific maintenance operations, such as replacing components, adjusting settings, etc. The real-time image information provided by the vision module ensures the accuracy and safety of the maintenance operations.

[0053] In some embodiments, step S340: The controller module controls the robot body to perform maintenance operations on the device under test under the guidance of the vision module, specifically including: Step S3401: Locate the oil leakage point of the device under test through a 3D camera, and determine the fault type by the pattern recognition module.

[0054] Step S3402: The controller module controls the robotic arm and manipulator to perform maintenance operations according to the fault type.

[0055] In this embodiment, the 3D camera can capture the 3D image data of the device under test, which includes the shape, texture, and depth information of the device surface. Through image processing algorithms, such as edge detection and feature matching, the specific location of the oil leakage point can be identified from the 3D image. Once the oil leakage point is located, the pattern recognition module will analyze the image of the oil leakage point using machine learning or deep learning algorithms. These algorithms have been trained to recognize different types of fault features, such as the shape, color, and diffusion pattern of the oil stain. Based on these features, the pattern recognition module will determine the specific type of oil leakage fault, such as seal damage, pipeline rupture, fuel tank leakage, etc. After receiving the fault type information output by the pattern recognition module, the controller module will analyze this information to determine the repair strategy to be taken. According to the fault type, the controller module will select appropriate repair tools (such as wrenches, screwdrivers, sealant guns, etc.), and control the robotic arm and manipulator to accurately move these tools to the oil leakage point. The robotic arm is responsible for moving the tool to the correct position, while the manipulator is responsible for operating these tools to perform specific repair actions, such as tightening screws, replacing seals, applying sealant, etc.

[0056] In some embodiments, as Figure 3 shown, step S340: After the step in which the controller module controls the robot body to perform a repair operation on the device under test under the guidance of the vision module, the following steps are further included: Step S350: After the repair is completed, monitor the repair status through the 3D camera and / or the monitoring platform.

[0057] Step S360: If it is detected that the data has been restored and there is no oil leakage, trigger the navigation perception module to collect the second environmental information through the vision module and the lidar; the navigation perception module generates a second dynamic navigation path based on the second environmental information and controls the mobile chassis to return to the initial position.

[0058] Step S370: If it is detected that the data has not been restored or there is an oil leakage, issue an alarm.

[0059] In this embodiment, after the repair is completed, monitor the repair status through the 3D camera and / or the monitoring platform This step aims to verify whether the repair operation is successful and ensure that the state of the device under test has returned to normal or the expected level. Utilize the high-precision imaging ability of the 3D camera to carefully inspect the repair area of the device under test, confirm whether the oil leakage point has been effectively sealed, and whether the device surface is clean without oil stains.

[0060] At the same time, the monitoring platform can continue to collect and analyze the oil chromatogram data to verify the repair effect at the data level. For example, the monitoring platform can detect whether the concentration of specific chemical components in the oil has returned to the normal range.

[0061] When the data from the 3D camera and / or the monitoring platform show that the repair is successful, that is, the data returns to normal and there is no oil leakage, the system will proceed to the next step. The visual module and the lidar are used to collect the second environmental information, which includes the spatial layout between the current position and the initial position, the location of obstacles, etc. Based on this environmental information, the navigation perception module generates a second dynamic navigation path, which is designed to guide the mobile chassis to return to the initial position safely and efficiently. The controller module controls the mobile chassis to move along the predetermined trajectory according to the generated navigation path until it returns to the initial position.

[0062] When the 3D camera or monitoring platform detects that the data has not returned to normal or there is an oil leak, the system will trigger an alarm mechanism. The system may sound an alarm, light or send a message to the operator, indicating that the maintenance operation was not successful or further inspection is required. The operator can take further actions based on the alarm information, such as re-performing the maintenance steps, calling professional maintenance personnel, etc.

[0063] In some specific embodiments, Figure 4 As shown in the figure, when the data processing module determines that the oil chromatogram monitoring device is leaking oil, the central control machine sends a command to the mobile chassis to control the mobile chassis to quickly move closer to the monitoring platform. During the movement, the two-dimensional camera and the three-dimensional camera continue to collect information about the surrounding environment, and provide accurate navigation for the movement of the mobile chassis through the navigation perception module, ensuring that the mobile chassis can reach the designated location safely and quickly.

[0064] When the mobile robot arrives at the designated position of the monitoring platform, the mobile chassis stops moving. The central control machine uses the precise positioning and visual guidance of the three-dimensional camera (depth camera) to determine the location of the oil leak. When the oil chromatography monitoring device leaks oil at the oil circuit connection on the main transformer side, the manipulator closes the online monitoring sampling valve clockwise under the guidance of the visual module, cuts off the loose part of the leaking joint, remakes the connection joint, and replaces the sealing gasket. After completion, wipe off the oil stains. Use the three-dimensional camera to check whether the valve is still leaking oil. If there is no oil leakage, the manipulator opens the online monitoring sampling valve under the visual module; if there is still oil leakage, it will immediately trigger an alarm and send a maintenance report to the manufacturer.

[0065] After the maintenance is completed, the central control machine uses the robot control module to orderly retract the robotic arm and command the mobile chassis to return to the starting position. During this process, the navigation perception module plays a role again to ensure the safe return of the mobile chassis. The entire system is restored to its initial state and is ready for the next round of monitoring and maintenance tasks, thereby ensuring that the entire system can operate continuously, stably and efficiently, effectively ensuring the normal operation of related equipment and the smooth progress of production activities.

[0066] In some other specific embodiments, Figure 4As shown in the figure, when the data processing module determines that the oil chromatogram monitoring device is leaking oil, the central control machine sends a command to the mobile chassis to control the mobile chassis to quickly move closer to the monitoring platform. During the movement, the two-dimensional camera and the three-dimensional camera continue to collect information about the surrounding environment, and provide accurate navigation for the movement of the mobile chassis through the navigation perception module, ensuring that the mobile chassis can reach the designated location safely and quickly.

[0067] When the mobile robot arrives at the designated position of the monitoring platform, the mobile chassis stops moving. The central control machine determines the location of the oil leak with the help of the precise positioning and visual guidance of the three-dimensional camera (depth camera). When oil leaks inside or around the oil chromatography online monitoring device, the central control machine starts the sampling function of the monitoring platform and observes the leakage during the sampling. In the case of loose joints due to vibration or aging, the manipulator tightens the joints along the visual guide line of the camera. Then, wipe off the oil stains and check whether there is still leakage. If so, take a photo of the leakage point with a camera and send it to the manufacturer, and turn off the valve and the online monitoring power supply.

[0068] The robot control module precisely controls the manipulator to carry out repair work on the faulty part. During the repair process, the pattern recognition module continuously evaluates and judges the fault repair status, and adjusts the operating parameters and actions of the manipulator according to the actual situation until it is confirmed that the fault has been successfully eliminated.

[0069] After the maintenance is completed, the central control machine retracts the robotic arm in an orderly manner through the controller module and directs the mobile chassis to return to the starting position. During this process, the navigation perception module plays a role again to ensure the safe return of the mobile chassis. The entire system is restored to its initial state and is ready for the next round of monitoring and maintenance tasks, thereby ensuring that the entire system can operate continuously, stably and efficiently, effectively ensuring the normal operation of related equipment and the smooth progress of production activities.

[0070] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An automatic oil chromatogram maintenance system based on a mobile robot, characterized in that, Applied to a device under test with a monitoring platform, including: A mobile robot, including: a mobile chassis, a robot body, a vision module, and a lidar; the robot body, the vision module, and the lidar are all arranged on the mobile chassis; A central control unit, arranged on the mobile chassis, including a data processing module, a navigation perception module, and a controller module; the data processing module is electrically connected to the monitoring platform, the navigation perception module is electrically connected to the vision module and the lidar through the data processing module, and the controller module is electrically connected to the robot body and the vision module through the data processing module; The data processing module is used to obtain the oil chromatogram data of the device under test monitored by the monitoring platform, and when detecting that the oil chromatogram data is abnormal, control the navigation perception module to collect environmental information through the vision module and the lidar. The mobile chassis, under the control of the navigation perception module, controls the mobile chassis to reach a specified position, and the controller module controls the robot body to repair the device under test under the guidance of the vision module.

2. The automatic oil chromatogram maintenance system based on a mobile robot according to claim 1, wherein, The vision module includes: A 3D camera and a camera bracket, the 3D camera is connected to the mobile chassis through the camera bracket, and the 3D camera is electrically connected to the controller module through the data processing module; A plurality of 2D cameras, evenly arranged around the mobile chassis, and the 2D cameras are electrically connected to the navigation perception module through the data processing module.

3. The oil chromatograph automatic maintenance system based on a mobile robot according to claim 2, wherein, The navigation perception module generates a dynamic navigation path of the mobile chassis by fusing the obstacle detection data of the lidar and the 360° environmental images of the plurality of 2D cameras.

4. The automatic oil chromatogram maintenance system based on a mobile robot according to claim 1, wherein The robot body includes: A robotic arm and a robot hand, one end of the robotic arm is connected to the robot hand, the other end of the robotic arm is connected to the mobile chassis, and both the robotic arm and the robot hand are electrically connected to the controller module.

5. The automatic oil chromatogram maintenance system based on a mobile robot according to any one of claims 1-4, characterized in that, The central control unit further includes: A pattern recognition module, electrically connected to the vision module through the data processing module, for locating the oil leakage point of the device under test and identifying the fault type.

6. The automatic oil chromatogram maintenance system based on a mobile robot according to any one of claims 1-4, characterized in that, The central control unit further includes: A communication module, electrically connected to the data processing module, the navigation perception module, and the controller module, for communicating with the monitoring platform, the mobile chassis, the robot body, the vision module, and the lidar.

7. A method for overhauling an oil chromatogram automatic overhaul system based on a mobile robot according to any one of claims 1-6, characterized in that, Including the following steps: Real-time collect the oil chromatogram data of the device under test through the monitoring platform and transmit it to the central control unit; The data processing module performs threshold analysis on the oil chromatogram data. If data abnormality is detected, trigger the navigation perception module to collect the first environmental information through the vision module and the lidar; The navigation perception module generates a first dynamic navigation path based on the first environmental information and controls the mobile chassis to move to a specified position of the monitoring platform; The controller module controls the robot body to perform a repair operation on the device under test under the guidance of the vision module.

8. The method according to claim 7, wherein The step that the controller module controls the robot body to perform a repair operation on the device under test under the guidance of the vision module includes: Locate the oil leakage point of the device to be measured through a 3D camera, and determine the fault type by the pattern recognition module; The controller module controls the manipulator and the robot hand to perform repair operations according to the fault type.

9. The method according to claim 8, characterized in that It also includes: After the repair is completed, monitor the repair status through the 3D camera and / or the monitoring platform; If it is detected that the data is restored and there is no oil leakage, trigger the navigation perception module to collect the second environmental information through the vision module and the lidar; The navigation perception module generates a second dynamic navigation path based on the second environmental information and controls the mobile chassis to return to the initial position.

10. The method according to claim 9, wherein It also includes: If it is detected that the data is not restored or there is oil leakage, an alarm is issued.

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