Distribution cable operation state monitoring device and method

Abstract

The invention provides a power distribution cable operation state monitoring device and method. The monitoring device comprises a multi-sensor monitoring module, a data processing module, a self-calibration module, a self-powered module, an early warning module and a diagnosis and repair module. The multi-sensor monitoring module comprises a cable partial discharge and fracture unit, a cable operation environment sensing unit and a cable built-in monitoring unit. The data processing module comprises a processing and analysis unit, a real-time judgment unit and an estimation unit; the self-calibration module comprises a multi-sensor fusion unit and a self-healing unit; according to the invention, various sensor data can be fused, the accuracy and reliability of the monitoring device are improved, and the possible limitation of a single sensor is avoided; a self-powered system is adopted, and a stable power supply can be provided for the monitoring device through an electromagnetic induction or photovoltaic technology; and when the monitoring device detects that the cable has a fault or an abnormal condition, measures can be automatically taken for repairing.

Description

Technical Field

[0001] The present invention relates to the technical field of cable monitoring, and in particular to a device and method for monitoring the operating status of a distribution cable. Background Art

[0002] With the development of science and technology, electric energy has become one of the indispensable energy sources for production, development and life. The use of electric energy is inseparable from the corresponding electric energy transmission, and the distribution cable is one of the most important equipment in the process of electric energy transmission. The economy and reliability of the operation of the distribution cable are mainly affected by the surrounding environment, operating conditions and laying methods. If there are problems, it will affect the current carrying capacity of the distribution cable, thus causing a transmission bottleneck and affecting the normal use of electric energy. Detecting the cable status is an important step in cable maintenance and repair.

[0003] Disadvantages of existing distribution cable condition monitoring devices:

[0004] 1. Most existing monitoring technologies only monitor the surface of the cable, the surrounding environment or the inside of the cable, which makes it difficult to provide comprehensive information for the safe operation of the cable and to detect potential problems in advance, resulting in frequent accidents.

[0005] 2. Most existing monitoring technologies rely on a single sensor for monitoring, which results in certain limitations of the unit sensor and reduces the accuracy and reliability of the monitoring device;

[0006] 3. Most existing monitoring devices require external power supply, which means that once the power is off, the monitoring of the cable will be forced to be interrupted, and the reliability and applicability of the device are poor;

[0007] 4. When the monitoring device detects a fault or abnormality in the cable, it is difficult to automatically take measures to assist in repairing the faulty cable, which reduces the efficiency of cable repair.

[0008] In view of this, the present invention proposes a device and method for monitoring the operating status of a distribution cable. Summary of the invention

[0009] The purpose of the present invention is to provide a distribution cable operation status monitoring device and method, so as to realize automatic monitoring and repair of distribution cable faults, improve the reliability and stability of the cable system, reduce power outage time, and ensure the safe operation of electrical equipment.

[0010] To achieve the above-mentioned purpose, the technical solution of the present invention is: a distribution cable operation status monitoring device; including a multi-sensor monitoring module, a data processing module, a self-calibration module, a self-power supply module, an early warning module, and a diagnosis and repair module;

[0011] The multi-sensor monitoring module is used to fuse multiple sensor data; the multi-sensor monitoring module includes a cable partial discharge and break unit, a cable operating environment sensing unit and a cable built-in monitoring unit;

[0012] The cable partial discharge and breakage unit is used to monitor abnormal conditions related to partial discharge or cable breakage during cable operation; the cable operation environment sensing unit uses optical fiber sensing technology to lay optical fibers around the cable and monitor the parameters of the cable surrounding environment in real time through optical fiber sensors; the cable built-in monitoring unit uses miniaturized sensors embedded in the cable to achieve real-time monitoring of the internal parameters of the cable, including temperature, humidity and voltage;

[0013] The data processing module includes a processing and analysis unit, a real-time judgment unit and an estimation unit;

[0014] The processing and analysis unit is used to perform intelligent analysis and processing on the monitored data, and the real-time judgment unit is used to accurately judge the operation status of the cable, and the estimation unit predicts the future operation trend of the cable based on historical data;

[0015] The self-calibration module includes a multi-sensor fusion unit and a self-healing unit;

[0016] The multi-sensor fusion unit is used to fuse redundant information from multiple sensors; the self-healing unit is used to automatically trigger a calibration process to calibrate the sensor when a sensor fails or data is abnormal;

[0017] The self-powered module is used to provide a stable power supply for the monitoring device;

[0018] The early warning module is used to combine real-time monitoring data and historical data to establish an intelligent early warning system and issue an alarm in a timely manner;

[0019] The diagnosis and repair module is used to provide detailed fault diagnosis information and automatically take measures to repair the cable when the monitoring device detects a fault or abnormality in the cable; the diagnosis and repair module is connected to the circuit breaker, the switch device of the backup power supply line and the communication network to realize the functions of automatically disconnecting the faulty cable, cutting off the power and switching the backup line.

[0020] Preferably, the cable partial discharge and breakage unit comprises a high-resolution optical imaging device, which utilizes high-resolution optical imaging technology to capture and analyze optical signals generated by tiny cracks on the cable surface and partial discharge.

[0021] Preferably, the cable partial discharge and breakage unit also includes an electromagnetic induction sensor and an acoustic wave sensor. The acoustic wave sensor is placed on the outside of the cable or embedded into the cable through miniaturization technology to monitor the acoustic wave signal inside the cable, and analyzes the frequency spectrum characteristics of the acoustic wave through a data processing module to detect abnormal vibration or arc breakdown inside the cable; the electromagnetic sensor is installed around the cable casing or other adjacent parts to detect electromagnetic signals around the cable; and the electromagnetic field related data is analyzed through the data processing module to detect cable operation abnormalities including cable overload and grounding fault.

[0022] Preferably, the self-healing unit includes two calibration methods: an online calibration method and a distributed calibration method implemented by an adaptive algorithm. The online calibration method is used to perform real-time calibration during the operation of the monitoring equipment, and the distributed calibration method is used to perform parallel calibration of multiple sensors in a large-scale monitoring device.

[0023] Preferably, the calculation formula of the adaptive algorithm is as follows:

[0024] C(x,t)=w(t)*(f(x)-g(x,t))+b(t)

[0025] Among them, C(x,t) is the calibrated sensor data, which means the result of sensor data x after calibration at time t; x is sensor data, which means the raw data collected from the sensor; t is time, which means the time when the calibration algorithm runs; w(t) is the calibration weight, which is adjusted dynamically over time; f(x) is the expected value function of sensor data, which means the expected value of sensor data under normal operating conditions; g(x,t) is the actual value function of sensor data, which means the actual value of sensor data at time t; b(t) is the calibration bias, which is adjusted dynamically over time;

[0026] The calibration weight w(t) and calibration bias b(t) are dynamically adjusted according to the difference between the actual value g(x,t) and the expected value f(x) of the sensor data, so that the calibration algorithm can adaptively respond to changes in sensor data.

[0027] Preferably, the self-calibration module also includes an active learning unit, a knowledge graph construction unit and an edge computing optimization unit. The active learning unit is used to selectively obtain the latest data and update the online calibration and distributed calibration methods; the knowledge graph construction unit is used to construct a knowledge graph of the monitoring device to assist the calibration algorithm in identifying and processing abnormal data; the edge computing optimization unit is used to optimize the computing efficiency of the calibration algorithm on the edge device to assist in achieving real-time calibration.

[0028] Preferably, the self-powered module adopts a self-powered system, which includes an electromagnetic induction device cooperating with the monitoring device, and the electromagnetic induction device is composed of a coil and a magnetic core. When the current in the cable changes, a changing magnetic field is generated around the cable. The magnetic field generates an induced current in the coil of the electromagnetic induction device. The coil converts the induced current into usable electrical energy through a conversion circuit, and the electrical energy is stored through an energy storage system for use by the monitoring device.

[0029] Preferably, the self-powered system further comprises a photovoltaic panel, which converts sunlight into electrical energy and stores the electrical energy via a battery or an energy storage device for use by the monitoring device.

[0030] The present invention also provides a monitoring method for a distribution cable operation status monitoring device, which is implemented using the above distribution cable operation status monitoring device and includes the following specific steps:

[0031] S1: The multi-sensor monitoring module integrates multiple sensor data;

[0032] S11: The acoustic wave signal inside the cable is monitored by an acoustic wave sensor, the electromagnetic field change around the cable is monitored by an electromagnetic sensor, the spectrum characteristics of the acoustic wave are analyzed by a data processing module, abnormal vibration or arc breakdown inside the cable is detected, and electromagnetic field related data is analyzed by a data processing module to detect abnormal cable operation including cable overload and ground fault;

[0033] S12: Arrange optical fibers around the cables and use optical fiber sensing technology to monitor the temperature and pressure parameters of the cable surrounding environment in real time through optical fiber sensors;

[0034] S13: Real-time monitoring of the temperature, humidity and voltage parameters inside the cable is achieved through the miniaturized sensors embedded inside the cable;

[0035] S2: The data processing module intelligently analyzes and processes the monitored data, determines the cable operation status, and predicts the future operation trend of the cable based on historical data;

[0036] S3: The self-calibration module integrates the redundant information from multiple sensors in the above steps, and automatically triggers the calibration process when a sensor fails or the data is abnormal; selectively obtains the latest data to update the relevant calibration parameters; builds a knowledge graph of the monitoring device to assist the calibration algorithm in identifying and processing abnormal data; optimizes the computational efficiency of the calibration algorithm on the edge device to assist in achieving real-time calibration;

[0037] S31: Calibrate the sensor device in real time during the operation of the monitoring device;

[0038] S32: Parallel calibration of multiple sensors in large-scale monitoring devices;

[0039] S4: The early warning module combines real-time monitoring data and historical data to establish an intelligent early warning system and issue alarms in a timely manner;

[0040] S5: When the diagnosis and repair module detects a fault or abnormality in the cable, it provides detailed fault diagnosis information and automatically takes measures to repair it;

[0041] S6: The self-power supply system of the power supply module provides power support for the devices and sensors in the above steps to achieve the self-power supply function.

[0042] Preferably, in step S5, the specific method is as follows:

[0043] S51: Fault location: The monitoring equipment first accurately locates the fault point of the distribution cable;

[0044] S52: Automatic power off; after determining the location of the fault point, the faulty cable is automatically disconnected or the power supply is cut off;

[0045] S53: Automatic switching; automatically switches the load to the backup cable or backup power supply line;

[0046] S54: Data recording and analysis; record detailed information of each fault, including time, location, and fault phenomenon, for subsequent data analysis and improvement.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] The present invention proposes a distribution cable operation status monitoring device and method. In actual application, the device can monitor the local discharge of the cable, the breakage of the cable, the temperature and pressure of the environment around the cable, and the temperature, humidity, voltage and other parameters inside the cable in real time, so as to discover potential problems in advance and avoid accidents, and provide more comprehensive information for the safe operation of the cable.

[0049] The present invention provides a distribution cable operation status monitoring device and method, which can fuse multiple sensor data in practical applications, improve the accuracy and reliability of the monitoring device, and avoid the limitations that may exist in a single sensor.

[0050] A distribution cable operation status monitoring device and method proposed in the present invention, when actually applied, adopts a self-powered system and can provide a stable power supply for the monitoring device through electromagnetic induction or photovoltaic technology, thereby solving the problem that traditional cable monitoring devices require external power supply and improving the reliability and applicability of the device.

[0051] A distribution cable operation status monitoring device and method proposed in the present invention introduces self-diagnosis and repair functions in practical applications. When the monitoring device detects a fault or abnormality in the cable, it can automatically take measures to repair it, or provide detailed fault diagnosis information to provide a basis for subsequent maintenance.

[0052] The present invention proposes a distribution cable operation status monitoring device and method, which, in actual application, can combine real-time monitoring data and historical data to establish an intelligent early warning system, can issue alarms in time and take emergency measures, effectively prevent the occurrence of cable accidents, and ensure the safe and stable operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is an overall architecture diagram of the distribution cable operation status monitoring device of the present invention;

[0054] Figure 2 The present invention is a flow chart of a monitoring method of a distribution cable operation status monitoring device. DETAILED DESCRIPTION

[0055] The following is combined with Figure 1-2 , the technical solution of the present invention is specifically described.

[0056] The present invention proposes a distribution cable operation status monitoring device, comprising a multi-sensor monitoring module, a data processing module, a self-calibration module, a self-power supply module, an early warning module, and a diagnosis and repair module;

[0057] The multi-sensor monitoring module is used to fuse data from multiple sensors to improve the accuracy and reliability of the monitoring device and avoid possible limitations of a single sensor;

[0058] Among them, the multi-sensor monitoring module includes a cable partial discharge and breakage unit, a cable operation environment sensing unit and a cable built-in monitoring unit. The cable partial discharge and breakage unit is used to monitor abnormal conditions related to partial discharge or cable breakage during cable operation, such as partial discharge, cable breakage, etc., so as to discover potential problems in advance and avoid accidents; the cable operation environment sensing unit uses optical fiber sensing technology to lay optical fibers around the cable, and uses optical fiber sensors to monitor the temperature, pressure and other parameters of the cable environment in real time, providing more comprehensive information for the safe operation of the cable; the miniaturized sensor unit realizes real-time monitoring of the temperature, humidity, voltage and other parameters inside the cable through a miniaturized sensor embedded in the cable, and such sensors perform destructive transformation on the cable; specifically, the miniaturized sensor is a small sensor embedded in the cable, which is used to monitor the internal parameters of the cable, such as temperature, humidity, voltage, etc. in real time; MEMS (micro-electromechanical system) technology is usually used to make the sensor miniaturized and integrated, so that it can be embedded in the internal structure of the cable for more accurate monitoring;

[0059] The cable partial discharge and fracture unit includes a high-resolution optical imaging device, which uses high-resolution optical imaging technology to achieve high-precision capture and analysis of optical signals generated by tiny cracks and partial discharge on the cable surface; the cable partial discharge and fracture unit also includes an electromagnetic induction sensor and an acoustic wave sensor, which monitors the acoustic wave signal inside the cable through the acoustic wave sensor, and uses the electromagnetic sensor to monitor the electromagnetic field changes around the cable. In combination with electromagnetic and acoustic wave technologies, the frequency spectrum characteristics of the acoustic wave are analyzed through a data processing module to detect abnormal vibration or arc breakdown inside the cable; the electromagnetic field related data are analyzed through the data processing module to find cable operation problems and realize the coupling monitoring of the acoustic wave signal and the electromagnetic signal inside the cable; wherein the acoustic wave sensor is placed on the outside of the cable or embedded in the cable through miniaturization technology, and is used to monitor the acoustic wave signal inside the cable, such as the vibration inside the cable or the acoustic wave generated by the arc breakdown; the electromagnetic sensor is installed around the cable casing or other adjacent parts, and the fault diagnosis is performed by detecting the changes in the electromagnetic signal and combining the acoustic wave data, thereby identifying problems such as cable overload and grounding fault.

[0060] The data processing module includes a processing and analysis unit, a real-time judgment unit and an estimation unit. The processing and analysis unit is used to perform intelligent analysis and processing on the monitored data, and the real-time judgment unit is used to accurately judge the operation status of the cable to reduce the false alarm rate. The estimation unit is used to predict the future operation trend of the cable based on historical data;

[0061] The self-calibration module includes a multi-sensor fusion unit and a self-healing unit. The multi-sensor fusion unit is used to fuse redundant information from multiple sensors to avoid the limitations that may exist in a single sensor and enhance calibration robustness. The self-healing unit is used to automatically trigger a calibration process and calibrate the sensor when a sensor fails or data is abnormal.

[0062] The self-healing unit includes two methods: online calibration and distributed calibration realized by adaptive algorithms. The online calibration method is used to calibrate in real time during the operation of the monitoring equipment without interrupting the monitoring; the distributed calibration method is used to calibrate multiple sensors in large-scale monitoring devices in parallel;

[0063] The calculation formula of the adaptive algorithm is as follows:

[0064] C(x,t)=w(t)*(f(x)-g(x,t))+b(t)

[0065] Among them, C(x,t) is the calibrated sensor data, which means the result of sensor data x after calibration at time t;

[0066] x is the sensor data, which means the raw data collected from the sensor;

[0067] t is time, indicating the time for which the calibration algorithm runs;

[0068] w(t) is the calibration weight, which is dynamically adjusted over time;

[0069] f(x) is the expected value function of the sensor data, which represents the expected value of the sensor data under normal operating conditions;

[0070] g(x,t) is the actual value function of the sensor data, which represents the actual value of the sensor data at time t;

[0071] b(t) is the calibration bias, which is adjusted dynamically over time;

[0072] The interaction rule in this formula is reflected in the dynamic adjustment of the calibration weight w(t) and the calibration bias b(t). These two parameters are dynamically adjusted according to the difference between the actual value g(x, t) and the expected value f(x) of the sensor data, so that the calibration algorithm can adaptively respond to changes in sensor data.

[0073] The self-calibration module also includes an active learning unit, a knowledge graph construction unit and an edge computing optimization unit. The active learning unit is used to selectively obtain the latest data and update the online calibration and distributed calibration methods; the knowledge graph construction unit is used to construct a knowledge graph of the monitoring device to assist the calibration algorithm in identifying and processing abnormal data; the edge computing optimization unit is used to optimize the computing efficiency of the calibration algorithm on the edge device to assist in achieving real-time calibration.

[0074] The self-powered module is used in conjunction with the monitoring device to provide a stable power supply for the monitoring device; the self-powered module adopts a self-powered system, which includes an electromagnetic induction device that cooperates with the device. The electromagnetic induction device is composed of a coil and a magnetic core. When the current in the cable changes, a changing magnetic field is generated around the cable. The magnetic field generates an induced current in the coil of the induction device. The coil converts and adjusts the induced current through a suitable circuit to convert it into usable electrical energy, and stores the electrical energy through an energy storage system (such as a battery or a supercapacitor) for use by the cable monitoring device. No additional energy supply is required, and only the current transmitted by the cable itself is required to achieve self-powering. The advantage of this type of design is that it does not require No additional energy supply is needed, and self-power can be achieved by utilizing the current transmitted by the cable itself. This simplifies the system structure, solves the problem that traditional cable monitoring devices require external power supply, and improves the reliability and applicability of the device. The self-powered system includes photovoltaic panels, which use light energy converted from sunlight to supply power. Photovoltaic panels convert sunlight into electrical energy, and store the electrical energy through batteries or energy storage devices for use by the cable monitoring device. A charging management system can be designed to adjust the charging and power supply strategy of the photovoltaic panels according to the intensity and time of sunlight to ensure continuous power supply to the monitoring device. The advantage is that no external power supply is required, and it only relies on solar energy, is suitable for outdoor environments, and is environmentally friendly and renewable.

[0075] The early warning module is used to combine real-time monitoring data and historical data to establish an intelligent early warning system, which can issue alarms in time, take emergency measures, effectively prevent the occurrence of cable accidents, and ensure the safe and stable operation of the power system;

[0076] The diagnosis and repair module is used to provide detailed fault diagnosis information and automatically take measures to repair the cable when the monitoring device detects a fault or abnormality in the cable, providing a basis for subsequent maintenance;

[0077] Specifically, the diagnosis and repair module is connected to the circuit breaker, the switch device of the backup power supply line and the communication network to realize the functions of automatically disconnecting the faulty cable, cutting off the power and switching the backup line; when the monitoring device detects the fault point, the diagnosis and repair module is linked with the power circuit breaker to automatically disconnect the faulty cable or cut off the power to prevent further damage or safety accidents; the diagnosis and repair module is connected to the switch device of the backup line to realize automatic switching after the fault occurs, and transfer the load to the backup cable or power supply line, so as to ensure the continuous operation of the power equipment; the diagnosis and repair module is connected to the power communication network so as to quickly send and receive instructions when a fault occurs, and coordinate other power grid equipment to switch and restore power supply.

[0078] The present invention also provides a monitoring method for the above-mentioned distribution cable operation status monitoring device, which specifically includes the following specific steps:

[0079] S1: The multi-sensor monitoring module is used to fuse multiple sensor data to improve the accuracy and reliability of the monitoring device and avoid the limitations that may exist in a single sensor;

[0080] S11: The acoustic wave signal inside the cable is monitored by an acoustic wave sensor, and the electromagnetic field changes around the cable are monitored by an electromagnetic sensor. The spectrum characteristics of the acoustic wave are analyzed by a data processing module to detect abnormal vibration or arc breakdown inside the cable. The electromagnetic field related data is analyzed by a data processing module to find problems such as cable overload and grounding fault, so as to find potential problems in advance and avoid accidents.

[0081] S12: Optical fibers are laid around the cables and optical fiber sensing technology is used to monitor the temperature, pressure and other parameters of the cable environment in real time through optical fiber sensors, providing more comprehensive information for the safe operation of the cables.

[0082] S13: Real-time monitoring of temperature, humidity, voltage and other parameters inside the cable is achieved through miniaturized sensors embedded inside the cable. Such sensors perform destructive modifications on the cable;

[0083] S2: The data processing module intelligently analyzes and processes the monitored data, accurately judges the cable operation status, reduces the false alarm rate, and predicts the future operation trend of the cable based on historical data;

[0084] S3: Fuse redundant information from multiple sensors in the above steps, and automatically trigger the calibration process when a sensor fails or data is abnormal; selectively obtain the latest data to update relevant calibration parameters; build a knowledge graph of monitoring devices to assist the calibration algorithm in identifying and processing abnormal data; optimize the computational efficiency of the calibration algorithm on edge devices to assist in achieving real-time calibration;

[0085] S31: Calibrate the sensor device in real time during the operation of the monitoring device;

[0086] S32: Parallel calibration of multiple sensors in large-scale monitoring devices;

[0087] S4: Combine real-time monitoring data and historical data to establish an intelligent early warning system that can issue alarms in a timely manner, take emergency measures, effectively prevent cable accidents, and ensure the safe and stable operation of the power system;

[0088] S5: When a cable fault or abnormality is detected, detailed fault diagnosis information is provided and measures are automatically taken to repair it, providing a basis for subsequent maintenance;

[0089] S51: Fault location: The monitoring equipment first accurately locates the fault point of the distribution cable. Specifically, the location of the fault point can be determined by monitoring the changes in parameters such as current, voltage, and temperature.

[0090] S52: Automatic power off; after determining the location of the fault point, the faulty cable is automatically disconnected or the power supply is cut off to avoid further damage or safety accidents;

[0091] S53: Automatic switching; automatically switches the load to the backup cable or backup power supply line to ensure that the affected equipment continues to operate normally;

[0092] S54: Data recording and analysis: record detailed information of each fault, including time, location, fault phenomenon, etc., for subsequent data analysis and improvement;

[0093] Through the above methods, automatic monitoring and repair of distribution cable faults can be achieved, the reliability and stability of the cable system can be improved, the power outage time can be reduced, and the safe operation of electrical equipment can be guaranteed;

[0094] S6: Provide power support for the devices and sensors in the above steps through the self-power supply system to achieve the self-power supply function.

[0095] In actual application, the device can monitor the local discharge of the cable, cable breakage, the temperature and pressure of the cable's surrounding environment, as well as the temperature, humidity, voltage and other parameters inside the cable in real time, so as to discover potential problems in advance, avoid accidents, and provide more comprehensive information for the safe operation of the cable; it can integrate data from multiple sensors to improve the accuracy and reliability of the monitoring device and avoid the limitations that may exist in a single sensor; the device adopts a self-powered system, which can provide a stable power supply for the monitoring device through electromagnetic induction or photovoltaic technology, solving the problem that traditional cable monitoring devices require external power supply and improving the reliability and applicability of the device; by introducing self-diagnosis and repair functions, when the monitoring device detects a fault or abnormality in the cable, it can automatically take measures to repair it, or provide detailed fault diagnosis information to provide a basis for subsequent maintenance; it can combine real-time monitoring data and historical data to establish an intelligent early warning system, which can issue alarms in time and take emergency measures to effectively prevent cable accidents and ensure the safe and stable operation of the power system.

[0096] 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 preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A distribution cable operation status monitoring device, characterized in that: It includes a multi-sensor monitoring module, a data processing module, a self-calibration module, a self-powered module, an early warning module, and a diagnosis and repair module; The multi-sensor monitoring module is used to fuse multiple sensor data; the multi-sensor monitoring module includes a cable partial discharge and break unit, a cable operating environment sensing unit and a cable built-in monitoring unit; The cable partial discharge and breakage unit is used to monitor abnormal conditions related to partial discharge or cable breakage during cable operation; the cable operation environment sensing unit uses optical fiber sensing technology to lay optical fibers around the cable and monitor the parameters of the cable surrounding environment in real time through optical fiber sensors; the cable built-in monitoring unit uses miniaturized sensors embedded in the cable to achieve real-time monitoring of the internal parameters of the cable, including temperature, humidity and voltage; The data processing module includes a processing and analysis unit, a real-time judgment unit and an estimation unit; The processing and analysis unit is used to perform intelligent analysis and processing on the monitored data, and the real-time judgment unit is used to accurately judge the operation status of the cable, and the estimation unit predicts the future operation trend of the cable based on historical data; The self-calibration module includes a multi-sensor fusion unit and a self-healing unit; The multi-sensor fusion unit is used to fuse redundant information from multiple sensors; the self-healing unit is used to automatically trigger a calibration process to calibrate the sensor when a sensor fails or data is abnormal; The self-powered module is used to provide a stable power supply for the monitoring device; The early warning module is used to combine real-time monitoring data and historical data to establish an intelligent early warning system and issue an alarm in a timely manner; The diagnosis and repair module is used to provide detailed fault diagnosis information and automatically take measures to repair the cable when the monitoring device detects a fault or abnormality in the cable; the diagnosis and repair module is connected to the circuit breaker, the switch device of the backup power supply line and the communication network to realize the functions of automatically disconnecting the faulty cable, cutting off the power and switching the backup line.

2. A distribution cable operation status monitoring device according to claim 1, characterized in that: The cable partial discharge and fracture unit comprises a high-resolution optical imaging device, which uses high-resolution optical imaging technology to capture and analyze optical signals generated by tiny cracks on the cable surface and partial discharge.

3. A distribution cable operation status monitoring device according to claim 2, characterized in that: The cable partial discharge and breakage unit also includes an electromagnetic induction sensor and an acoustic wave sensor. The acoustic wave sensor is placed on the outside of the cable or embedded into the cable through miniaturization technology, and is used to monitor the acoustic wave signal inside the cable. The frequency spectrum characteristics of the acoustic wave are analyzed through a data processing module to detect abnormal vibration or arc breakdown inside the cable. The electromagnetic sensor is installed around the cable casing or other adjacent parts to detect electromagnetic signals around the cable. The electromagnetic field related data is analyzed through the data processing module to detect cable operation abnormalities including cable overload and grounding fault.

4. A distribution cable operation status monitoring device according to claim 1, characterized in that: The self-healing unit includes two calibration modes: an online calibration mode and a distributed calibration mode realized by an adaptive algorithm. The online calibration mode is used to perform real-time calibration during the operation of the monitoring equipment, and the distributed calibration mode is used to perform parallel calibration of multiple sensors in a large-scale monitoring device.

5. A distribution cable operation status monitoring device according to claim 4, characterized in that: The calculation formula of the adaptive algorithm is as follows: C(x,t)=w(t)*(f(x)-g(x,t))+b(t) Among them, C(x,t) is the calibrated sensor data, which means the result of sensor data x after calibration at time t; x is sensor data, which means the raw data collected from the sensor; t is time, which means the time when the calibration algorithm runs; w(t) is the calibration weight, which is adjusted dynamically over time; f(x) is the expected value function of sensor data, which means the expected value of sensor data under normal operating conditions; g(x,t) is the actual value function of sensor data, which means the actual value of sensor data at time t; b(t) is the calibration bias, which is adjusted dynamically over time; The calibration weight w(t) and calibration bias b(t) are dynamically adjusted according to the difference between the actual value g(x,t) and the expected value f(x) of the sensor data, so that the calibration algorithm can adaptively respond to changes in sensor data.

6. A distribution cable operation status monitoring device according to claim 5, characterized in that: The self-calibration module also includes an active learning unit, a knowledge graph construction unit and an edge computing optimization unit. The active learning unit is used to selectively obtain the latest data and update the online calibration and distributed calibration methods; the knowledge graph construction unit is used to construct a knowledge graph of the monitoring device to assist the calibration algorithm in identifying and processing abnormal data; The edge computing optimization unit is used to optimize the computing efficiency of the calibration algorithm on the edge device and assist in achieving real-time calibration.

7. A distribution cable operation status monitoring device according to claim 1, characterized in that: The self-powered module adopts a self-powered system, which includes an electromagnetic induction device that cooperates with the monitoring device. The electromagnetic induction device is composed of a coil and a magnetic core. When the current in the cable changes, a changing magnetic field is generated around the cable. The magnetic field generates an induced current in the coil of the electromagnetic induction device. The coil converts the induced current into usable electrical energy through a conversion circuit, and the electrical energy is stored through an energy storage system for use by the monitoring device.

8. A distribution cable operation status monitoring device according to claim 7, characterized in that: The self-powered system also includes a photovoltaic panel, which converts sunlight into electrical energy and stores the electrical energy through a battery or an energy storage device for use by the monitoring device.

9. A monitoring method for a distribution cable operation status monitoring device, characterized in that: The method is implemented by using a distribution cable operation status monitoring device as described in any one of claims 1 to 8, and includes the following specific steps: S1: The multi-sensor monitoring module integrates multiple sensor data; S11: The acoustic wave signal inside the cable is monitored by an acoustic wave sensor, the electromagnetic field change around the cable is monitored by an electromagnetic sensor, the spectrum characteristics of the acoustic wave are analyzed by a data processing module, abnormal vibration or arc breakdown inside the cable is detected, and electromagnetic field related data is analyzed by a data processing module to detect abnormal cable operation including cable overload and ground fault; S12: Arrange optical fibers around the cables and use optical fiber sensing technology to monitor the temperature and pressure parameters of the cable surrounding environment in real time through optical fiber sensors; S13: Real-time monitoring of temperature, humidity and voltage parameters inside the cable is achieved through the miniaturized sensors embedded inside the cable; S2: The data processing module intelligently analyzes and processes the monitored data, determines the cable operation status, and predicts the future operation trend of the cable based on historical data; S3: The self-calibration module integrates the redundant information from multiple sensors in the above steps, and automatically triggers the calibration process when a sensor fails or the data is abnormal; selectively obtains the latest data to update the relevant calibration parameters; builds a knowledge graph of the monitoring device to assist the calibration algorithm in identifying and processing abnormal data; optimizes the computational efficiency of the calibration algorithm on the edge device to assist in achieving real-time calibration; S31: Calibrate the sensor device in real time during the operation of the monitoring device; S32: Parallel calibration of multiple sensors in large-scale monitoring devices; S4: The early warning module combines real-time monitoring data and historical data to establish an intelligent early warning system and issue alarms in a timely manner; S5: When the diagnosis and repair module detects a fault or abnormality in the cable, it provides detailed fault diagnosis information and automatically takes measures to repair it; S6: The self-power supply system of the power supply module provides power support for the devices and sensors in the above steps to achieve the self-power supply function.

10. The monitoring method of a distribution cable operation status monitoring device according to claim 9, characterized in that: In step S5, the specific method is as follows: S51: Fault location: The monitoring equipment first accurately locates the fault point of the distribution cable; S52: Automatic power off; after determining the location of the fault point, the faulty cable is automatically disconnected or the power supply is cut off; S53: Automatic switching; automatically switches the load to the backup cable or backup power supply line; S54: Data recording and analysis; record detailed information of each fault, including time, location, and fault phenomenon, for subsequent data analysis and improvement.

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