Fault detection system suitable for distribution line

Abstract

The invention relates to the technical field of fault detection of distribution lines, in particular to a fault detection system suitable for a distribution line. Comprising an infrared thermal imaging detection module, a current real-time monitoring module, an ultrasonic fault positioning module, an electromagnetic wave interference detection module, a deep learning analysis module, an unmanned inspection module, an environment monitoring module and an interactive alarm module. The system integrates various monitoring technologies, can comprehensively and accurately reflect the state of a line, can monitor the state of the line in real time, can immediately give an alarm and process once an abnormality or a fault is found, can accurately position a fault point through an ultrasonic fault positioning technology, improves the maintenance efficiency, and reduces the maintenance cost. The deep learning advanced technology is used for intelligent analysis of monitoring data, the line state can be preliminarily judged, a basis is provided for maintenance decision making, unmanned line inspection is achieved through application of the unmanned aerial vehicle technology, and the inspection efficiency and safety are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fault detection for distribution lines, and specifically to a fault detection system applicable to distribution lines. Background Art

[0002] Distribution lines are the lines in the power system responsible for delivering electric energy from substations or distribution stations to the user side, including overhead lines and cable lines of various voltage levels, and are an important part of power supply.

[0003] However, generally, for traditional detection work, it is necessary for staff to conduct inspections along the line regularly or irregularly, discover line abnormalities through observation, listening, and touching, install fault indicators on the line, and when a line fault occurs, the indicator will emit a signal to help staff quickly locate the fault point, and judge whether there is an insulation damage fault by measuring the insulation resistance of the line. Therefore, it is inevitable that manual inspection is time-consuming and laborious, and is greatly affected by weather and terrain factors. Manual inspection and fault indicators may be interfered by subjective factors or environmental factors, resulting in inaccurate fault location, and it is difficult to achieve real-time monitoring of the line status. It often takes a long time to discover and handle after a fault occurs.

[0004] Based on this, the present invention provides a fault detection system applicable to distribution lines to solve the above-mentioned technical problems. Summary of the Invention

[0005] The purpose of the present invention is to provide a fault detection system applicable to distribution lines to solve the problems raised in the above background art.

[0006] To achieve the above purpose, the present invention provides the following technical solutions: A fault detection system applicable to distribution lines includes an infrared thermal imaging detection module, a current real-time monitoring module, an ultrasonic fault location module, an electromagnetic wave interference detection module, a deep learning analysis module, an unmanned inspection module, an environmental monitoring module, and an interactive alarm module; The infrared thermal imaging detection module is used for thermal imaging acquisition and generation of a thermal map; The current real-time monitoring module is used for Rogowski coil detection and current data analysis; The ultrasonic fault location module is used for ultrasonic wave emission and ultrasonic wave reception analysis; The electromagnetic wave interference detection module is used for detecting electromagnetic wave interference around the distribution line and identifying the interference source; The deep learning analysis module is used for image recognition and data fusion analysis; The unmanned inspection module is used for drone control and transmission of inspection data back; The environmental monitoring module is used to monitor the temperature, humidity and meteorological data analysis of the environment around the power distribution line; The interactive alarm module is used for data display and alarm notification.

[0007] Preferably, the infrared thermal imaging detection module further includes a thermal imaging acquisition unit and a thermal map generation unit; The thermal imaging acquisition unit, through an integrated infrared thermal imaging probe, is used to receive the infrared radiation generated by an object, convert it into a temperature lattice through a budget amplification circuit, and perform signal processing through a dedicated infrared imaging algorithm to achieve the function of high-precision temperature measurement; The thermal map generation unit is used to transmit the collected temperature lattice to a tablet computer through a USB to TTL circuit, generate an infrared thermodynamic image through software parsing and chromaticity matching, and ensure the clarity and accuracy of the thermal map through an image rendering algorithm.

[0008] Preferably, the current real-time monitoring module further includes a Rogowski coil detection unit and a current data analysis unit; The Rogowski coil detection unit is externally connected to a detachable Rogowski coil, used to detect the real-time current of the wire to be measured, convert the current signal into a voltage signal, and achieve accurate current measurement through a current-voltage conversion algorithm; The current data analysis unit is used to detect the voltage signal through the ADC channel of the STM32 chip, obtain the actual current through ratio calculation, and send it to the cloud platform through a 4G module, and perform real-time monitoring and anomaly detection on the current data through a data analysis algorithm.

[0009] Preferably, the ultrasonic fault location module further includes an ultrasonic emission unit and an ultrasonic reception and analysis unit; The ultrasonic emission unit emits ultrasonic signals through an ultrasonic sensor, used to detect the fault point in the power distribution line, and ensure the stability and accuracy of the signal through an ultrasonic emission algorithm; The ultrasonic reception and analysis unit receives the reflected ultrasonic signals, calculates the position of the fault point through the time difference, and realizes the accurate positioning of the fault point through an ultrasonic positioning algorithm.

[0010] Preferably, the electromagnetic wave interference detection module further includes an electromagnetic wave sensor unit and an interference source identification unit; The electromagnetic wave sensor unit detects the electromagnetic wave interference situation around the power distribution line through an electromagnetic wave sensor, and realizes the real-time monitoring of electromagnetic wave interference through an electromagnetic wave detection algorithm; The interference source identification unit is used to analyze the detected electromagnetic wave interference, identify possible interference sources, and improve the accuracy of interference source identification through a pattern recognition algorithm.

[0011] Preferably, the deep learning analysis module further includes an image recognition unit and a data fusion analysis unit; The image recognition unit uses deep learning algorithms to recognize and analyze infrared thermal imaging images, which are used to detect abnormal hot spots in the line. Through image recognition algorithms, a preliminary judgment of line faults is achieved; The data fusion analysis unit is used to fuse and analyze multi-source data of infrared thermal imaging, current monitoring, and ultrasonic positioning, improve the accuracy and reliability of fault detection, and achieve comprehensive processing of multi-source data through data fusion algorithms.

[0012] Preferably, the unmanned inspection module further includes a drone control unit and an inspection data transmission unit; The drone control unit is equipped with an infrared thermal imaging camera and an ultrasonic sensor device on the drone, which is used to inspect the distribution line. Through drone control technology, autonomous flight and inspection task planning of the drone are achieved; The inspection data transmission unit is used to transmit the data collected during the drone inspection to the ground station or cloud platform in real time. Through wireless communication technology, the timeliness and integrity of the data are ensured.

[0013] Preferably, the environmental monitoring module further includes a temperature and humidity sensor unit and a meteorological data analysis unit; The temperature and humidity sensor unit monitors the temperature and humidity conditions of the environment around the distribution line through temperature and humidity sensors. Through temperature and humidity detection algorithms, real-time monitoring of environmental parameters is achieved; The meteorological data analysis unit is used to analyze the monitored meteorological data and evaluate its impact on the operation of the distribution line. Through meteorological data analysis algorithms, the practicality of environmental parameter monitoring is improved.

[0014] Preferably, the interaction and alarm module further includes a data display unit and an alarm notification unit; The data display unit is used to display the data collected and analyzed by each module, as well as the location and type information of the fault point on a tablet computer. Through graphical interface design, the readability and usability of the data are improved; The alarm notification unit is used to give an alarm by sound and light when a line fault or abnormality is detected, and notify relevant personnel by text message and email. Through alarm notification algorithms, the timely transmission and processing of fault information are ensured.

[0015] Compared with the prior art, the beneficial effects of the present invention are: The present invention integrates a variety of monitoring technologies, which can comprehensively and accurately reflect the status of the line, can monitor the line status in real time, and once an abnormality or fault is detected, it can immediately give an alarm and handle it. Through the ultrasonic fault location technology, the system can accurately locate the fault point, improve the maintenance efficiency, and use the advanced deep learning technology to intelligently analyze the monitoring data, which can initially judge the line status and provide a basis for maintenance decision-making. The application of unmanned aerial vehicle technology realizes the unmanned inspection of the line, improves the inspection efficiency and safety. At the same time, the system is modularly designed, easy to expand and upgrade, and can adapt to the development needs of future power systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a topology diagram of a fault detection system applicable to a distribution line according to the present invention; Figure 2 It is a flowchart of a fault detection method applicable to a distribution line according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] Next, in combination with the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention. Embodiment

[0018] Please refer to Figure 1 , the present invention proposes a fault detection system applicable to a distribution line, including an infrared thermal imaging detection module, a current real-time monitoring module, an ultrasonic fault location module, an electromagnetic wave interference detection module, a deep learning analysis module, an unmanned inspection module, an environmental monitoring module, and an interactive alarm module; Among them, it should also be noted that the infrared thermal imaging detection module is used for thermal imaging acquisition and thermogram generation, the current real-time monitoring module is used for Rogowski coil detection and current data analysis, the ultrasonic fault location module is used for ultrasonic emission and ultrasonic reception analysis, the electromagnetic wave interference detection module is used for detecting the electromagnetic wave interference around the distribution line and identifying the interference source, the deep learning analysis module is used for image recognition and data fusion analysis, the unmanned inspection module is used for unmanned aerial vehicle control and inspection data transmission, the environmental monitoring module is used for monitoring the temperature and humidity conditions of the environment around the distribution line and meteorological data analysis, and the interactive alarm module is used for data display and alarm notification.

[0019] In this embodiment, it should also be noted that the infrared thermal imaging detection module further includes a thermal imaging acquisition unit and a thermogram generation unit; Furthermore, the thermal imaging acquisition unit integrates an infrared thermal imaging probe, which is used to receive the infrared radiation generated by an object, convert it into a temperature lattice through a budget amplification circuit, and perform signal processing through a dedicated infrared imaging algorithm to achieve high-precision temperature measurement functions; Furthermore, the thermogram generation unit is used to transmit the collected temperature lattice to a tablet computer through a USB to TTL circuit, generate an infrared thermodynamic image through software parsing and chromaticity matching, and ensure the clarity and accuracy of the thermogram through an image rendering algorithm.

[0020] In this embodiment, it should also be noted that the current real-time monitoring module further includes a Rogowski coil detection unit and a current data analysis unit; Furthermore, the Rogowski coil detection unit is externally connected to a detachable Rogowski coil, which is used to detect the real-time current of the wire to be measured, convert the current signal into a voltage signal, and achieve accurate current measurement through a current-voltage conversion algorithm; Furthermore, the current data analysis unit is used to detect the voltage signal through the ADC channel of the STM32 chip, obtain the actual current through ratio calculation, and send it to the cloud platform through a 4G module. Through data analysis algorithms, real-time monitoring and anomaly detection of current data are performed.

[0021] In this embodiment, it should also be noted that the ultrasonic fault location module further includes an ultrasonic emission unit and an ultrasonic reception and analysis unit; Furthermore, the ultrasonic emission unit emits ultrasonic signals through an ultrasonic sensor to detect the fault point in the power distribution line, and ensures the stability and accuracy of the signal through an ultrasonic emission algorithm; Furthermore, the ultrasonic reception and analysis unit receives the reflected ultrasonic signal, calculates the position of the fault point through the time difference, and achieves precise positioning of the fault point through an ultrasonic positioning algorithm.

[0022] In this embodiment, it should also be noted that the electromagnetic interference detection module further includes an electromagnetic wave sensor unit and an interference source identification unit; Furthermore, the electromagnetic wave sensor unit detects the electromagnetic wave interference situation around the power distribution line through an electromagnetic wave sensor, and achieves real-time monitoring of electromagnetic wave interference through an electromagnetic wave detection algorithm; Furthermore, the interference source identification unit is used to analyze the detected electromagnetic wave interference, identify possible interference sources, and improve the accuracy of interference source identification through pattern recognition algorithms.

[0023] In this embodiment, it should also be noted that the deep learning analysis module further includes an image recognition unit and a data fusion analysis unit; Further, the image recognition unit uses deep learning algorithms to recognize and analyze infrared thermal imaging images, which are used to detect abnormal hot spots in the line. Through the image recognition algorithm, a preliminary judgment of the line fault is realized; Further, the data fusion and analysis unit is used to fuse and analyze multi-source data of infrared thermal imaging, current monitoring, and ultrasonic positioning, improve the accuracy and reliability of fault detection, and realize the comprehensive processing of multi-source data through the data fusion algorithm.

[0024] In this embodiment, it should also be noted that the unmanned inspection module further includes a drone control unit and an inspection data transmission unit; Further, the drone control unit is equipped with an infrared thermal imaging camera and an ultrasonic sensor device by the drone, which is used to inspect the distribution line. Through drone control technology, the autonomous flight and inspection task planning of the drone are realized; Further, the inspection data transmission unit is used to transmit the data collected during the drone inspection to the ground station or cloud platform in real time. Through wireless communication technology, the real-time and integrity of the data are ensured.

[0025] In this embodiment, it should also be noted that the environmental monitoring module further includes a temperature and humidity sensor unit and a meteorological data analysis unit; Further, the temperature and humidity sensor unit monitors the temperature and humidity of the environment around the distribution line through temperature and humidity sensors. Through the temperature and humidity detection algorithm, the real-time monitoring of environmental parameters is realized; Further, the meteorological data analysis unit is used to analyze the monitored meteorological data and evaluate its impact on the operation of the distribution line. Through the meteorological data analysis algorithm, the practicality of environmental parameter monitoring is improved.

[0026] In this embodiment, it should also be noted that the interactive alarm module further includes a data display unit and an alarm notification unit; Further, the data display unit is used to display the data collected and analyzed by each module, as well as the location and type information of the fault point on the tablet computer. Through the graphical interface design, the readability and usability of the data are improved; Further, the alarm notification unit is used to alarm by sound and light when a line fault or abnormality is detected, and notify relevant personnel by text message and email. Through the alarm notification algorithm, the timely transmission and processing of fault information are ensured. Embodiment

[0027] Please refer to Figure 2 , in practical applications, based on the method of the fault detection system applicable to the distribution line, specifically, it includes the following steps: Start the system: (1)System power on: Connect the system power supply to ensure that all modules can work properly; System initialization: After the system starts, perform self-check and initialization operations, including hardware initialization, software initialization, etc.; Module standby: After each module completes initialization, enter the standby state and wait for instructions to perform subsequent operations; Instruction input interface preparation: The system prepares an interface to receive external instructions, such as keyboard input, remote control signals, etc.; System status display: Display the current system status on the control terminal (such as a computer or tablet), including whether each module is online, whether the system is ready, etc.; Waiting for instructions: The system is in a standby state, waiting for the operator to input instructions to start working; Parallel start of infrared thermal imaging and current monitoring: (1)Start of infrared thermal imaging detection module: Start of infrared probe: Start the infrared thermal imaging probe to start receiving the infrared radiation of the line; Temperature dot matrix generation: Convert the received infrared radiation into a temperature dot matrix to prepare for the subsequent generation of a thermal map; Thermal map generation: Convert the temperature dot matrix into an infrared thermodynamic image through a dedicated algorithm and software; (2)Start of real-time current monitoring module: Connection of Rogowski coil: Ensure that the Rogowski coil is correctly connected to the wire to be measured; Real-time current detection: Detect the real-time current of the wire through the Rogowski coil and convert the current signal into a voltage signal; Data analysis: Analyze the converted voltage signal, calculate the actual current value, and perform real-time monitoring; Environmental monitoring and electromagnetic wave interference detection: (1)Start of environmental monitoring module: Start of sensors: Start the temperature and humidity sensors and meteorological sensors to start monitoring environmental parameters; Data acquisition: Real-time acquisition of temperature, humidity and meteorological data, such as temperature, humidity, wind speed, wind direction, etc.; Data analysis: Analyze the collected environmental data and evaluate its impact on the operation of the power distribution line; (2)Start of electromagnetic wave interference detection module: Start of electromagnetic wave sensor: Start the electromagnetic wave sensor to start detecting the electromagnetic wave interference situation around the power distribution line; Interference signal acquisition: Real-time acquisition of electromagnetic wave interference signals and perform preliminary processing; Interference source identification: Analyze the collected interference signals and try to identify possible interference sources; Preparation for Ultrasonic Fault Location: (1)Preparation of Ultrasonic Transmitting Unit: Transmitter Inspection: Check whether the ultrasonic transmitter is working properly; Signal Setting: Set parameters such as the frequency and amplitude of the ultrasonic transmission signal; (2)Preparation of Ultrasonic Receiving Unit: Receiver Inspection: Check whether the ultrasonic receiver is working properly; Receiving Setting: Set the sensitivity, filtering parameters, etc. of the ultrasonic receiver; (3)Completion of Fault Location Preparation: Ensure that both the ultrasonic transmitting and receiving units are ready for fault location operations; Data Fusion and Deep Learning Analysis: (1)Data Reception and Integration: Data Reception: Receive data from modules such as infrared thermal imaging, current monitoring, environmental monitoring, and electromagnetic interference detection; Data Integration: Integrate the received data to form a unified dataset; (2)Deep Learning Analysis: Image Recognition: Use deep learning algorithms to identify and analyze infrared thermal imaging images, and detect abnormal hot spots in the circuit; Data Fusion Analysis: Integrate and analyze multi-source data such as infrared thermal imaging, current monitoring, and ultrasonic location to improve the accuracy and reliability of fault detection; Preliminary Judgment: Based on the analysis results, preliminarily judge the circuit status, such as whether there is a fault and the type of fault; (3)Abnormal Handling: Abnormal Data Identification: Identify abnormal data or suspected fault points during the analysis process; Trigger for Further Detection: If there is abnormal data or suspected fault points, trigger further detection operations, such as starting the unmanned inspection module, etc.; Start of Unmanned Inspection: (1)Drone Preparation: Drone Inspection: Check whether the drone is in good condition, such as battery power, flight control system, etc.; Equipment Mounting: Mount devices such as infrared thermal imaging cameras and ultrasonic sensors on the drone; (2)Inspection Task Planning: Route Planning: Plan the flight route of the drone according to the layout of the distribution line and inspection requirements; Task Setting: Set the inspection tasks of the drone, such as taking infrared thermal imaging images, collecting ultrasonic signals, etc.; (3)Drone Start and Inspection: Drone takeoff: Start the drone and take off according to the planned route; Inspection process control: During the inspection process, control the flight attitude and speed of the drone in real time to ensure the smooth progress of the inspection task; Data transmission: The drone transmits the collected data to the ground station or cloud platform in real time for subsequent analysis and processing; Fault location and alarm: (1) Ultrasonic fault location: Receive reflected signal: Receive the reflected ultrasonic signal through the ultrasonic receiving unit; Time difference calculation: Calculate the position of the fault point based on the time difference between the transmitted and received signals; Fault point determination: Combine other detection data to determine the specific position and type of the fault point; (2) Alarm information display: Fault information generation: Generate fault information based on the fault location result, including the fault point position, type, etc.; Information display: Display the fault information on the tablet for the operator to view and process; (3) Alarm notification: Sound and light alarm: Conduct on-site alarm through sound, light, etc. to alert the operator; SMS and email notification: Notify relevant personnel through SMS, email, etc. to ensure the timely transmission and processing of fault information; Data processing and follow-up actions: (1) Data storage and analysis: Data storage: Store the data collected by each module and the analysis results in the cloud platform or ground station; Data analysis: Further analyze the stored data, extract useful information, and provide a basis for subsequent maintenance and repair; (2) Maintenance and repair measures: Maintenance plan formulation: Formulate a maintenance plan based on the fault location result and analysis data; Maintenance implementation: Perform maintenance operations according to the maintenance plan to repair the fault point; Maintenance measures: Take necessary maintenance measures based on the analysis results to prevent similar faults from occurring; System reset and standby: (1) System reset: Module reset: Perform a reset operation on each module to restore its initial state; System status check: After the reset is completed, check whether the system status is normal; (2) System standby: Standby mode setting: Set the system to standby mode and wait for the next command input; Standby state monitoring: Real-time monitor the system status to ensure that the system is in a normal standby state.

[0028] Through the above steps, the present invention integrates a variety of monitoring technologies, can comprehensively and accurately reflect the status of the line, can monitor the line status in real time, once an abnormality or fault is found, can immediately give an alarm and handle it. Through the ultrasonic fault location technology, the system can accurately locate the fault point, improve the maintenance efficiency. Using the advanced deep learning technology to intelligently analyze the monitoring data, can initially judge the line status and provide a basis for maintenance decision-making. The application of the unmanned aerial vehicle technology realizes the unmanned inspection of the line, improves the inspection efficiency and safety. At the same time, the modular design of the system is easy to expand and upgrade, and can adapt to the development needs of future power systems.

[0029] In summary, the distribution line fault detection system of the present invention has significant technical advantages and practical values, can effectively improve the operation reliability and safety of the distribution line, and provide a strong guarantee for the stable operation of the power system.

[0030] In the description of this specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0031] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. This specification selects and specifically describes these embodiments to better explain the principle and practical application of the present invention, so that those skilled in the relevant art can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A fault detection system suitable for a power distribution line, characterized in that: Including infrared thermal imaging detection module, current real-time monitoring module, ultrasonic fault location module, electromagnetic interference detection module, deep learning analysis module, unmanned inspection module, environmental monitoring module, interactive alarm module; The infrared thermal imaging detection module is used for thermal imaging acquisition and thermal map generation; The current real-time monitoring module is used for Rogowski coil detection and current data analysis; The ultrasonic fault location module is used for ultrasonic emission and ultrasonic reception analysis; The electromagnetic wave interference detection module is used to detect electromagnetic wave interference around the power distribution line and identify the interference source; The deep learning analysis module is used for image recognition and data fusion analysis; The unmanned inspection module is used for drone control and inspection data transmission; The environmental monitoring module is used to monitor the temperature and humidity conditions of the environment surrounding the power distribution line and analyze meteorological data; The interactive alarm module is used for data display and alarm notification.

2. A fault detection system suitable for distribution lines according to claim 1, characterized in that: The infrared thermal imaging detection module also includes a thermal imaging acquisition unit and a thermal map generation unit; The thermal imaging acquisition unit is integrated with an infrared thermal imaging probe to receive infrared radiation generated by an object and convert it into a temperature dot matrix through a budget amplifier circuit; The thermal map generation unit is used to transmit the collected temperature dot matrix to the tablet computer through the USB to TTL circuit, and generate an infrared thermodynamic image through software analysis and color matching.

3. A fault detection system suitable for distribution lines according to claim 2, characterized in that: The current real-time monitoring module also includes a Rogowski coil detection unit and a current data analysis unit; The Rogowski coil detection unit is externally connected to a detachable Rogowski coil, and is used to detect the real-time current of the conductor to be tested and convert the current signal into a voltage signal; The current data analysis unit is used to detect the voltage signal through the ADC channel of the STM32 chip, obtain the actual current through the transformation ratio calculation, and send it to the cloud platform through the 4G module. Through the data analysis algorithm, the current data is monitored in real time and abnormality detection is performed.

4. A fault detection system suitable for distribution lines according to claim 3, characterized in that: The ultrasonic fault location module also includes an ultrasonic transmitting unit and an ultrasonic receiving and analyzing unit; The ultrasonic transmitting unit transmits ultrasonic signals through ultrasonic sensors to detect fault points in the power distribution line; The ultrasonic receiving and analyzing unit receives the reflected ultrasonic signal and calculates the position of the fault point through the time difference.

5. A fault detection system suitable for power distribution lines according to claim 4, characterized in that: The electromagnetic wave interference detection module also includes an electromagnetic wave sensor unit and an interference source identification unit; The electromagnetic wave sensor unit detects electromagnetic wave interference around the power distribution line through an electromagnetic wave sensor; The interference source identification unit is used to analyze the detected electromagnetic wave interference and identify possible interference sources.

6. A fault detection system suitable for power distribution lines according to claim 5, characterized in that: The deep learning analysis module also includes an image recognition unit and a data fusion analysis unit; The image recognition unit uses a deep learning algorithm to recognize and analyze infrared thermal imaging images to detect abnormal hot spots in the line; The data fusion and analysis unit is used to fuse and analyze multi-source data including infrared thermal imaging, current monitoring, and ultrasonic positioning.

7. A fault detection system suitable for power distribution lines according to claim 6, characterized in that: The unmanned inspection module also includes a drone control unit and an inspection data return unit; The drone control unit is used to inspect the power distribution lines by carrying an infrared thermal imaging camera and an ultrasonic sensor device on the drone; The inspection data feedback unit is used to transmit the data collected during the drone inspection process to the ground station or cloud platform in real time through wireless communication technology.

8. A fault detection system suitable for power distribution lines according to claim 7, characterized in that: The environmental monitoring module also includes a temperature and humidity sensor unit and a meteorological data analysis unit; The temperature and humidity sensor unit monitors the temperature and humidity conditions of the environment surrounding the power distribution line through the temperature and humidity sensor; The meteorological data analysis unit is used to analyze the monitored meteorological data and evaluate its impact on the operation of the distribution line.

9. A fault detection system suitable for power distribution lines according to claim 8, characterized in that: The interactive alarm module also includes a data display unit and an alarm notification unit; The data display unit is used to display the data collected and analyzed by each module, as well as the location and type information of the fault point on the tablet computer; The alarm notification unit is used to alarm by sound or light when a line fault or abnormality is detected, and to notify relevant personnel by text message or email.

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