Booster station intelligent inspection robot system based on machine vision

Abstract

The invention provides a booster station intelligent inspection robot system based on machine vision. The booster station intelligent inspection robot system comprises an image acquisition module used for acquiring image information in a specified area of a booster station, and a sensing detection module used for detecting operation data of a specific point in the booster station; the control module comprises a data receiving unit, a data analysis unit and an instruction output unit, the data receiving unit is used for receiving the image information and the operation data, the data analysis unit is used for analyzing the image information and the operation data, and the instruction output unit is used for generating a corresponding control instruction according to an analysis result and outputting the control instruction to the inspection robot. Therefore, the inspection robot is controlled to inspect the booster station. The problems that due to the fact that existing manual routing inspection is low in routing inspection efficiency, incomplete in coverage, single in detection means, high in safety risk and weak in data analysis capacity, missing inspection and misjudgment are prone to occurring, data integration capacity is lacked, trend prediction of the equipment state cannot be achieved, and effective support is difficult to provide for operation and maintenance decisions are solved.

Description

Technical Field

[0001] This invention relates to the field of intelligent inspection technology for substations, and in particular to an intelligent inspection robot system for substations based on machine vision. Background Technology

[0002] With the continuous advancement of "smart power plant" construction in my country, the traditional manual inspection model is no longer sufficient to meet the requirements of modern power systems for safety, reliability, and efficiency. As a critical node in the transmission of electricity from thermal power plants, step-up substations are characterized by a wide variety of equipment, harsh operating environments, and rapid fault propagation. Current manual inspection methods have the following drawbacks: 1. Low inspection efficiency and incomplete coverage: The substation occupies a large area and the equipment is widely distributed. Manual inspection is time-consuming and labor-intensive, and is prone to problems such as missed inspections and misjudgments. Second, the detection methods are limited: they mainly rely on visual observation or portable instrument measurement, lacking continuity, real-time capability and data integration ability, and cannot achieve trend prediction of equipment status. Third, high safety risks: Inspection personnel need to work in dangerous environments such as high pressure, high temperature, and humidity, and are more prone to safety accidents in severe weather such as rain, snow, and sandstorms. Fourth, weak data analysis capabilities: Data collected in the traditional way is isolated and scattered, lacking a unified management and intelligent analysis mechanism, making it difficult to provide effective support for operation and maintenance decisions.

[0003] Therefore, this application proposes a machine vision-based intelligent inspection robot system for booster stations to overcome the above-mentioned shortcomings. Summary of the Invention

[0004] The purpose of this invention is to solve the problems of existing manual inspections, which are characterized by low inspection efficiency, incomplete coverage, single detection methods, high safety risks, and weak data analysis capabilities. These problems lead to missed inspections and misjudgments, lack of data integration capabilities, inability to predict equipment status trends, and difficulty in providing effective support for operation and maintenance decisions.

[0005] To achieve the above objectives, the present invention provides a machine vision-based intelligent inspection robot system for substations, comprising: An inspection robot is configured to move along a preset inspection path within the substation. The inspection robot is equipped with an image acquisition module and a sensor detection module. The image acquisition module is used to acquire image information within a specified area of ​​the substation, and the sensor detection module is used to detect the operating data of specific points within the substation. The control module includes a data receiving unit, a data analysis unit, and an instruction output unit. The data receiving unit is used to receive image information and operating data. The data analysis unit is used to analyze the image information and operating data. The instruction output unit is used to generate corresponding control instructions based on the analysis results and output them to the inspection robot to control the inspection robot to perform inspection operations on the booster station.

[0006] Optionally, the intelligent inspection robot system for the substation also includes a drive module, which includes an inspection track laid in the substation and a drive slide mounted on the inspection track. The inspection robot is mounted on the drive slide and is driven to move along the inspection track by the drive slide.

[0007] Optionally, the image acquisition module includes a visible light PTZ camera and an infrared thermal imager. The high-definition camera can capture visible light images of a designated area of ​​the booster station, while the infrared thermal imager can scan the designated area of ​​the booster station and acquire infrared thermal images.

[0008] Optionally, the sensing and detection module includes a concentration detection unit and an obstacle avoidance detection unit. The concentration detection unit is used to detect the gas concentration at a specific location within the booster station, and the obstacle avoidance detection unit is used to enable the inspection robot to sense obstacles during inspection and avoid them.

[0009] Optionally, the intelligent inspection robot system for the booster station also includes a wireless power supply module, which includes a wireless charging compartment electrically connected to the command output unit. The wireless charging compartment is used to supply power to the inspection robot.

[0010] Optionally, the substation is equipped with an environmental monitoring module, which is electrically connected to the control module to monitor and provide feedback on the operating environment within the substation in real time.

[0011] Optionally, the environmental monitoring module includes several temperature sensors, several humidity sensors, several wind speed sensors, several illuminance sensors, and several gas sensors. The temperature sensors are used to detect the temperature in a specific area within the substation, the humidity sensors are used to detect the humidity in a specific area within the substation, the wind speed sensors are used to detect the wind speed and direction in a specific area within the substation, the illuminance sensors are used to detect the illuminance in a specific area within the substation, and the gas sensors are used to detect the gas concentration in a specific area within the substation.

[0012] Optionally, the environmental monitoring module further includes an environmental prediction unit, which is used to predict the environmental change data of the booster station within a specified time in the future based on the current environmental data of the booster station and feed it back to the data receiving unit so as to regulate the instructions output by the instruction output unit.

[0013] Optionally, the control module also includes an alarm response unit, which is used to issue alarms for abnormal operating status of the booster station and inspection robot based on the abnormal data analyzed by the data analysis unit, and output the alarm information to the command output unit to send alarm commands to the booster station or inspection robot.

[0014] Optionally, the intelligent inspection robot system for the booster station also includes a back-end intelligent operation and maintenance management platform. The back-end intelligent operation and maintenance management platform is connected to the control module and is used to manage inspection tasks, store historical data, display analysis results, and generate operation and maintenance reports.

[0015] The beneficial effects of this invention are as follows: This invention proposes a machine vision-based intelligent inspection robot system for substations. The system comprises an inspection robot configured to move along a preset inspection path within the substation. The robot is equipped with an image acquisition module and a sensor detection module. The image acquisition module acquires image information within a designated area of ​​the substation, while the sensor detection module detects operational data at specific points within the substation. A control module is also included, comprising a data receiving unit, a data analysis unit, and a command output unit. The data receiving unit receives image information and operational data, the data analysis unit analyzes the image information and operational data, and the command output unit generates corresponding control commands based on the analysis results and outputs them to the inspection robot to control its inspection operations at the substation. Compared to existing manual inspection methods, this invention achieves full coverage and multi-method detection of the substation, avoiding blind spots and missed detections caused by single detection methods in manual inspections. Furthermore, the data analysis unit integrates and analyzes the data, providing effective support for the operation and maintenance decisions of the command output unit.

[0016] Furthermore, this invention includes an environmental prediction unit. This unit predicts environmental changes at the substation within a specified timeframe based on the current environmental data and feeds these changes back to the data receiving unit. This allows for the regulation of commands output by the command output unit, thereby enabling effective prediction of environmental change trends at the substation and providing strong support for its stable operation.

[0017] As can be seen from the above, the technical solution of the present invention can effectively solve the problems of low inspection efficiency, incomplete coverage, single detection method, high safety risk and weak data analysis capability of existing manual inspection, which leads to easy omissions and misjudgments, lack of data integration capability, inability to predict the trend of equipment status, and difficulty in providing effective support for operation and maintenance decisions.

[0018] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0019] The present invention can be better understood by referring to the following description taken in conjunction with the accompanying drawings, in which the same or similar reference numerals are used throughout the drawings to denote the same or similar parts.

[0020] Figure 1 This is a schematic diagram of a machine vision-based intelligent inspection robot system for booster stations, according to an embodiment of the present invention. Detailed Implementation

[0021] To enable those skilled in the art to more fully understand the technical solutions of the present invention, exemplary embodiments of the present invention will be described more comprehensively and in detail below with reference to the accompanying drawings. Obviously, the one or more embodiments of the present invention described below are merely one or more specific ways to implement the technical solutions of the present invention, and are not exhaustive. It should be understood that other ways belonging to a general inventive concept can be used to implement the technical solutions of the present invention, and should not be limited to the embodiments described exemplary. Based on one or more embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] Reference Figure 1 The present invention provides a machine vision-based intelligent inspection robot system for booster stations, comprising: An inspection robot is configured to move along a preset inspection path within the substation. The inspection robot is equipped with an image acquisition module and a sensor detection module. The image acquisition module is used to acquire image information within a specified area of ​​the substation, and the sensor detection module is used to detect the operating data of specific points within the substation. The control module includes a data receiving unit, a data analysis unit, and an instruction output unit. The data receiving unit is used to receive image information and operating data. The data analysis unit is used to analyze the image information and operating data. The instruction output unit is used to generate corresponding control instructions based on the analysis results and output them to the inspection robot to control the inspection robot to perform inspection operations on the booster station.

[0023] In one embodiment, the intelligent inspection robot system for the substation further includes a drive module, which includes an inspection track laid in the substation and a drive slide mounted on the inspection track. The inspection robot is mounted on the drive slide to move along the inspection track via the drive slide.

[0024] Specifically, the inspection track can be a modular track connected by bolts or clips. Its layout can be customized according to the substation layout. By determining the turning radius and the inspection robot's power parameters, it can be ensured that the inspection robot can accurately reach each inspection task point. The specific structure and principle of driving the slide to move on the inspection track are existing technologies, such as linear modules, and will not be elaborated further in this invention.

[0025] In one embodiment, the image acquisition module includes a visible light PTZ camera and an infrared thermal imager. The high-definition camera can capture visible light images of a designated area of ​​the booster station, and the infrared thermal imager can scan the designated area of ​​the booster station and acquire infrared thermal images.

[0026] Specifically, when the inspection robot moves to designated areas within the substation, such as electrical equipment, disconnect switches, control cabinets, and areas where personnel are active, it can acquire visible light images of instrument panel data, disconnect switch status, indicator light changes, and personnel activity by photographing the instrument panels of electrical equipment, disconnect switches, control cabinet indicator lights, and moving personnel. Based on these visible light images: On the one hand, it facilitates the control module to receive and analyze dashboard data: for pointer instruments, the data analysis unit combines semantic segmentation and multi-angle filtering algorithms to identify the pointer direction, uses Hough transform and perspective correction technology to eliminate distortion, and finally calculates the reading through angle calculation; for digital instruments, the data analysis unit uses OCR combined with target detection technology to first identify the instrument type and text area, and then parse the numerical value, unit and range information. Universal recognition can be achieved without pre-setting the instrument model, thereby realizing non-contact high-precision automatic reading of various instrument data, completely eliminating human error, and improving the consistency and reliability of data acquisition by the data receiving unit.

[0027] On the other hand, it facilitates the control module to analyze and judge the status of the disconnector: the data analysis unit uses image recognition technology to analyze the positional features of the mechanical structure of the disconnector, and combines it with the disconnector status information pre-stored in the control module to determine whether the current status is "closed" or "open". It also supports one station and multiple groups, and multi-station synchronous detection, thereby realizing fully automatic and highly reliable identification of the status of key switching equipment, providing real-time and accurate status feedback for scheduling and operation and maintenance, preventing operational accidents caused by misjudgment of status, and enhancing the safety of system operation.

[0028] On the other hand, it facilitates the control module to analyze and judge the operating status of the control cabinet: the data analysis unit performs preprocessing such as noise reduction and contrast enhancement on the visible light images of the indicator lights, uses a deep learning object detection model to identify the position and status of the indicator lights, distinguishes between constant on, constant off, flashing and color changes, and matches them with the preset standard logic rules in the control module to determine whether there is an abnormality, thereby realizing continuous dynamic monitoring of the control cabinet status, timely capturing abnormal signals, improving the ability to perceive the operating status of the equipment, and assisting in quickly locating the source of the fault.

[0029] On the other hand, it facilitates the control module's monitoring of personnel activities: the data analysis unit analyzes and judges the compliance of personnel activities based on the personnel activity standards preset by the control module, such as judging whether there are cases of not wearing or improperly wearing masks, identifying whether the clothing is compliant, identifying typical smoking actions and postures, and analyzing changes in human posture to judge whether there have been falls, electric shocks, or other situations. This enables timely monitoring of personnel behavior, and once a violation is detected, it is immediately fed back to the control module so that safety supervisors can intervene in a timely manner, significantly improving the level of on-site safety management.

[0030] Furthermore, the acquisition of infrared thermal images allows for the periodic scanning of surface temperature distribution on equipment within the substation, obtaining thermal images and marking the areas with the highest temperatures. This enables timely responses to issues such as poor contact or overload in components like transformers, busbar connectors, and switch contacts within the substation, preventing localized overheating that could lead to insulation damage or even fire and explosion. Consequently, it allows for early detection and precise location of thermal defects in substation equipment, supporting preventative maintenance, avoiding major equipment damage or power outages caused by overheating, and extending equipment lifespan.

[0031] The specific structure and principles of visible light pan-tilt cameras and infrared thermal imagers are existing technologies, and will not be elaborated further in this invention.

[0032] In one embodiment, the sensing and detection module includes a concentration detection unit and an obstacle avoidance detection unit. The concentration detection unit is used to detect the gas concentration at a specific location within the booster station, and the obstacle avoidance detection unit is used to enable the inspection robot to sense obstacles during inspection and avoid them.

[0033] In one specific embodiment, the concentration detection unit is a sulfur hexafluoride concentration detector. Specifically, sulfur hexafluoride is the insulating medium for high-voltage equipment in a booster station. Once it leaks, it not only affects the performance of the equipment but also contributes to the greenhouse effect, harming the environment and human health. Traditional detection methods have low sensitivity and slow response.

[0034] This invention integrates a sulfur hexafluoride (SF6) concentration detector onto an inspection robot to monitor changes in SF6 concentration in a booster station in real time. This enables online and continuous monitoring of SF6 gas leaks, improves detection sensitivity and response speed, ensures stable equipment insulation performance, and reduces environmental pollution and health risks.

[0035] In one specific embodiment, the obstacle avoidance detection unit is an ultrasonic obstacle avoidance sensor. Specifically, due to the complex terrain of the substation, which contains obstacles, ditches, temporary construction equipment, etc., the inspection robot may collide or get stuck if it does not have an effective obstacle avoidance mechanism, affecting the execution of the inspection task.

[0036] This invention equips an inspection robot with an ultrasonic obstacle avoidance sensor, allowing the sensitivity to be set according to the specific requirements of the substation. The data receiving unit samples the sensor signals in real time, calculates distance values, and immediately executes emergency braking when an obstacle is detected at a distance below a set threshold. It then sends a status message to the command output unit requesting manual verification. This ensures the inspection robot's safe operation in complex environments, prevents equipment damage or task interruption due to collisions, and improves the system's robustness and reliability.

[0037] In one embodiment, the inspection robot is equipped with a voice intercom module, which issues a voice warning after the robot detects an abnormal state. Specifically, by incorporating a voice intercom module into the inspection robot, maintenance personnel can quickly arrive at the site after the robot detects an abnormal state and issues a voice warning. Back-end technical personnel can provide remote guidance via visible light camera footage and the voice channel, enabling remote and on-site collaborative operations. This enhances the collaboration between the inspection robot and the control module, improves the efficiency and accuracy of fault handling, and plays a crucial role, especially in troubleshooting complex faults, compensating for the lack of experience among frontline personnel.

[0038] In one embodiment, the intelligent inspection robot system for the substation further includes a wireless power replenishment module. This module includes a wireless charging compartment electrically connected to the command output unit, which replenishes the robot's power. Specifically, the robot can automatically return to the wireless charging compartment adapted to its inspection track based on its remaining power, completing the entire wireless charging process without human intervention. This enables autonomous energy management throughout the robot's lifecycle, ensuring long-term continuous operation and improving the overall automation level of the system.

[0039] In one embodiment, an environmental monitoring module is installed in the substation. The environmental monitoring module is electrically connected to the control module to monitor and provide feedback on the operating environment in the substation in real time.

[0040] In one specific embodiment, the environmental monitoring module includes several temperature sensors, several humidity sensors, several wind speed sensors, several illuminance sensors, and several gas sensors. The temperature sensors detect the temperature in a specific area within the substation; the humidity sensors detect the humidity in the same area; the wind speed sensors detect the wind speed and direction; the illuminance sensors detect the light intensity; and the gas sensors detect the gas concentration. Specifically, by deploying these sensors within a designated area of ​​the substation, a comprehensive understanding of the substation's operating environment can be achieved. This provides environmental variable references for equipment operation status analysis, helps to more accurately determine the causes of anomalies, and improves the scientific rigor of the command output unit's decision-making.

[0041] In one embodiment, the environmental monitoring module further includes an environmental prediction unit, which is used to predict environmental change data of the booster station within a specified time in the future based on the current environmental data of the booster station and feed it back to the data receiving unit so as to regulate the instructions output by the instruction output unit.

[0042] Specifically, the environmental prediction unit uses a time series analysis algorithm, combining historical data with real-time sampled values, to predict the range of environmental data fluctuations within a specified future time period, such as 1 hour. If it predicts that high temperature and humidity will occur, which is detrimental to equipment heat dissipation, the instruction output unit can activate the corresponding heat dissipation equipment in advance to improve local heat dissipation conditions. This enables proactive management of environmental data, optimizes equipment operating conditions, and extends service life.

[0043] In one embodiment, the control module further includes an alarm response unit. The alarm response unit is used to issue alarms for abnormal operating states of the booster station and inspection robot based on abnormal data analyzed by the data analysis unit, and outputs the alarm information to the command output unit to send alarm commands to the booster station or inspection robot. Specifically, by setting up the alarm response unit, multiple data sources such as visible light images, infrared thermal images, several temperature sensors, several humidity sensors, several wind speed sensors, several illuminance sensors, and several gas sensors can be integrated to establish an intelligent alarm detection algorithm based on historical and real-time data.

[0044] By combining robot-level alarms or alarm response unit alarms, the false alarm rate is significantly reduced, alarm reliability is improved, maintenance burden is reduced, and an accurate and efficient anomaly response mechanism is achieved.

[0045] In one embodiment, the intelligent inspection robot system for the booster station also includes a back-end intelligent operation and maintenance management platform. This platform communicates with the control module and is used to manage inspection tasks, store historical data, display analysis results, and generate operation and maintenance reports. Specifically, the back-end intelligent operation and maintenance management platform adopts a B / S architecture design, including a task scheduling subsystem, a data storage subsystem, a visual monitoring subsystem, an alarm management subsystem, and a report output subsystem. The task scheduling subsystem supports setting inspection plans by period or event trigger. The data storage subsystem uses a hybrid database structure: a file database for storing videos and images, a relational database for managing structured information such as equipment status, temperature, and gas concentration, and a real-time database for processing dynamic streaming data. The visual monitoring subsystem provides functions such as a panoramic view of the booster station, robot position tracking, and heat map overlay. The report output subsystem can automatically generate equipment health assessment reports, fault trend charts, and inspection coverage statistics tables as needed. This achieves digital and traceable management of the entire inspection process, providing management with scientific decision-making support and promoting the transformation of the operation and maintenance model from experience-driven to data-driven.

[0046] It is worth noting that the back-end intelligent operation and maintenance management platform is implemented based on the host computer.

[0047] In one embodiment, the intelligent inspection robot system for the booster station further includes an autonomous navigation and path planning module, which generates a specific inspection path so that the inspection robot can perform inspections and locate itself according to the specific inspection path.

[0048] In one specific embodiment, the autonomous navigation and path planning module includes a laser SLAM positioning unit, an electronic map building unit, and a dynamic path planning algorithm unit. The laser SLAM positioning unit can scan the internal environment of the substation using the laser radar on the inspection robot to locate the inspection robot. The electronic map building unit is used to update and build an electronic map of the substation in real time based on historical inspection data. The dynamic path planning algorithm unit is used to generate a specific inspection path based on the electronic map and the preset distribution of inspection task points, so that the inspection robot can perform inspections and locate itself according to the specific inspection path.

[0049] Specifically, the laser SLAM positioning unit uses the lidar on the inspection robot to scan the internal environment of the booster station in real time, and combines wheel speed encoder and IMU inertial measurement data to achieve centimeter-level positioning accuracy; the high-precision electronic map construction unit continuously optimizes the three-dimensional spatial model of the booster station based on historical inspection data; the dynamic path planning algorithm unit generates the shortest conflict-free path according to the preset inspection task point distribution using A* or Dijkstra algorithm, and supports automatic route adjustment and detour when obstacles are detected.

[0050] This enables the inspection robot to drive stably and stop accurately in complex electrical environments, avoiding missed or false inspections due to positioning deviations, and improving the automation and reliability of inspection operations.

[0051] In one embodiment, the intelligent inspection robot system for the substation also includes a personnel intrusion detection module. This module identifies unauthorized personnel entering designated areas of the substation based on image information. Specifically, the personnel intrusion detection module uses a deep learning object detection model to identify human silhouettes and their movement trajectories in a visible light image stream, determining whether the person has entered a fenced-off restricted area or equipment operating area. When illegal intrusion is confirmed, the module immediately activates an audible and visual alarm, automatically captures multiple frames of images and short video clips, and uploads them to the backend intelligent operation and maintenance management platform for evidence preservation. This enhances the substation's security capabilities, prevents external interference from causing safety accidents, and ensures the safe operation of power facilities.

[0052] In one embodiment, the intelligent inspection robot system for the substation also includes a cable interlayer infrared temperature monitoring module. This module is installed in the cable interlayer of the substation to continuously monitor changes in the cable sheath temperature. Specifically, the cable interlayer infrared temperature monitoring module consists of a fixed integrated infrared camera with automatic focusing and temperature field mapping functions. It periodically scans cable joints, bends, and other areas prone to overheating, generating a complete thermal image and marking the highest temperature area. The data analysis unit compares historical temperature rise curves with thresholds to determine if there is a risk of localized overheating and issues tiered warnings. This enables 24 / 7 monitoring of the cable's operating status within the enclosed space, effectively preventing fires caused by insulation aging or poor contact, and improving the inherent safety level of the power distribution system.

[0053] In one embodiment, the wireless power replenishment module includes a charging status monitoring unit, which is used to monitor voltage, current, power factor and temperature parameters in real time during the wireless charging process, and issue an alarm when abnormalities occur.

[0054] Specifically, the charging status monitoring unit is deployed inside the wireless charging cabin and collects electrical parameters during the energy transmission process through non-contact sensors. Once charging interruption, efficiency decline, or excessive temperature occurs, it immediately reports through the communication link and triggers the alarm response unit to prompt maintenance personnel to check the charging interface or power line, thereby improving the stability and safety of the wireless charging system and preventing robot shutdown due to energy supply failure.

[0055] This invention proposes a machine vision-based intelligent inspection robot system for substations. The system comprises an inspection robot configured to move along a preset inspection path within the substation. The robot is equipped with an image acquisition module and a sensor detection module. The image acquisition module acquires image information within a designated area of ​​the substation, while the sensor detection module detects operational data at specific points within the substation. A control module is also included, comprising a data receiving unit, a data analysis unit, and a command output unit. The data receiving unit receives image information and operational data, the data analysis unit analyzes the image information and operational data, and the command output unit generates corresponding control commands based on the analysis results and outputs them to the inspection robot to control its inspection operations at the substation. Compared to existing manual inspection methods, this invention achieves full coverage and multi-method detection of the substation, avoiding blind spots and missed detections caused by single detection methods in manual inspections. Furthermore, the data analysis unit integrates and analyzes the data, providing effective support for the operation and maintenance decisions of the command output unit.

[0056] Furthermore, this invention includes an environmental prediction unit. This unit predicts environmental changes at the substation within a specified timeframe based on the current environmental data and feeds these changes back to the data receiving unit. This allows for the regulation of commands output by the command output unit, thereby enabling effective prediction of environmental change trends at the substation and providing strong support for its stable operation.

[0057] While one or more embodiments of the present invention have been described above, those skilled in the art will recognize that the present invention can be implemented in any other form without departing from its spirit and scope. Therefore, the embodiments described above are illustrative and not restrictive, and many modifications and substitutions will be apparent to those skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.

Claims

1. A machine vision-based intelligent inspection robot system for booster stations, characterized in that, include: An inspection robot is configured to move along a preset inspection path within the substation. The inspection robot is equipped with an image acquisition module and a sensor detection module. The image acquisition module is used to acquire image information within a specified area of ​​the substation, and the sensor detection module is used to detect the operating data of specific points within the substation. The control module includes a data receiving unit, a data analysis unit, and an instruction output unit. The data receiving unit is used to receive image information and operating data. The data analysis unit is used to analyze the image information and operating data. The instruction output unit is used to generate corresponding control instructions based on the analysis results and output them to the inspection robot to control the inspection robot to perform inspection operations on the booster station.

2. The intelligent inspection robot system for booster stations based on machine vision according to claim 1, characterized in that, The intelligent inspection robot system for the booster station also includes a drive module, which includes an inspection track laid in the booster station and a drive slide mounted on the inspection track. The inspection robot is mounted on the drive slide so that it can be driven to move along the inspection track by the drive slide.

3. The intelligent inspection robot system for booster stations based on machine vision according to claim 2, characterized in that, The image acquisition module includes a visible light PTZ camera and an infrared thermal imager. The high-definition camera can capture visible light images of a designated area of ​​the booster station, while the infrared thermal imager can scan a designated area of ​​the booster station and acquire infrared thermal images.

4. The intelligent inspection robot system for booster stations based on machine vision according to claim 3, characterized in that, The sensing and detection module includes a concentration detection unit and an obstacle avoidance detection unit. The concentration detection unit is used to detect the gas concentration at a specific location within the booster station, and the obstacle avoidance detection unit is used to enable the inspection robot to sense obstacles during inspection and avoid them.

5. The intelligent inspection robot system for booster stations based on machine vision according to claim 4, characterized in that, The intelligent inspection robot system for the booster station also includes a wireless power supply module, which includes a wireless charging compartment electrically connected to the command output unit. The wireless charging compartment is used to supply power to the inspection robot.

6. The intelligent inspection robot system for booster stations based on machine vision according to claim 5, characterized in that, The booster station is equipped with an environmental monitoring module, which is electrically connected to the control module to monitor and provide feedback on the operating environment within the booster station in real time.

7. The intelligent inspection robot system for booster stations based on machine vision according to claim 6, characterized in that, The environmental monitoring module includes several temperature sensors, several humidity sensors, several wind speed sensors, several illuminance sensors, and several gas sensors. The temperature sensors are used to detect the temperature in a specific area within the substation, the humidity sensors are used to detect the humidity in a specific area within the substation, the wind speed sensors are used to detect the wind speed and direction in a specific area within the substation, the illuminance sensors are used to detect the illuminance in a specific area within the substation, and the gas sensors are used to detect the gas concentration in a specific area within the substation.

8. The intelligent inspection robot system for booster stations based on machine vision according to claim 7, characterized in that, The environmental monitoring module also includes an environmental prediction unit, which is used to predict the environmental change data of the booster station within a specified time in the future based on the current environmental data of the booster station and feed it back to the data receiving unit so as to regulate the instructions output by the instruction output unit.

9. The intelligent inspection robot system for booster stations based on machine vision according to claim 8, characterized in that, The control module also includes an alarm response unit, which is used to issue alarms for abnormal operating status of the booster station and inspection robot based on the abnormal data analyzed by the data analysis unit, and output the alarm information to the command output unit to send alarm commands to the booster station or inspection robot.

10. The intelligent inspection robot system for booster stations based on machine vision according to claim 9, characterized in that, The intelligent inspection robot system for the booster station also includes a back-end intelligent operation and maintenance management platform. The back-end intelligent operation and maintenance management platform is connected to the control module and is used to manage inspection tasks, store historical data, display analysis results, and generate operation and maintenance reports.

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