Electrical secondary circuit defect systematic detection method

Abstract

The invention relates to the technical field of electrics, and discloses an electrical secondary circuit defect systematic detection method, which comprises the following steps: step 1, exquisite construction of an adaptive function detection device, step 2, deep fusion of a novel sensor and a leading edge detection technology, and step 3, robust construction and efficient cooperative operation of a distributed detection system. The method has the advantages that by means of fusion of a multi-element high-precision sensor and an advanced detection technology, the insulation detection precision reaches the millimeter level, the electrical parameter error is reduced by 80%, milliampere-level current changes can be captured, potential faults can be accurately pulled out, a self-adaptive mechanism covers electrical and environmental factors, and under the conditions that the temperature ranges from-40 DEG C to 70 DEG C, the humidity ranges from 10% to 95% and 0.05-15 times of rated load fluctuation, the insulation detection precision reaches the millimeter level; intelligent parameter adjustment is achieved, the false alarm rate is reduced to be within 2% from 20%, a distributed architecture is combined with intelligent diagnosis, the detection period is shortened to 10 minutes per time, fault positioning is shortened to 30 minutes from 4 hours, and the first-aid repair time efficiency and the power supply reliability are greatly improved.

Description

Technical Field

[0001] The invention relates to the field of electrical technology, and in particular to a method for systematically detecting defects in an electrical secondary circuit. Background Art

[0002] In the operation architecture of modern power systems, electrical secondary circuits play an indispensable role as the key link for monitoring the operation status of primary equipment, executing control instructions, and triggering system protection actions. Traditional detection solutions for electrical secondary circuits have exposed multiple shortcomings, which seriously restrict the process of refined operation and maintenance of power systems.

[0003] On the one hand, the established detection parameter settings cannot meet the needs of complex and changeable working scenarios. With the large fluctuations in ambient temperature and humidity and the drastic changes in circuit load during peak and valley periods, conventional detection methods often turn a blind eye to potential faults caused by weak current distortion under low load and insulation performance degradation in high humidity environments due to parameter mismatch, resulting in a significant reduction in detection accuracy. On the other hand, the old sensor technology is limited by the bottleneck of principle accuracy, and is unable to extract small fault features under the increasingly compact spatial layout of secondary circuits. In addition, the detection method is single and relies heavily on indirect judgment based on electrical parameters, making it difficult to directly address the problems of microscopic damage inside the insulation and hidden looseness of connectors. The overall detection process is lengthy, tedious, and lacks timeliness. At the same time, the centralized detection layout is complex and the wiring is intricate. A failure in a cable or detection node can easily induce "blindness" in systemic detection, and troubleshooting is like looking for a needle in a haystack, hindering the promotion of efficient operation and maintenance. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above-mentioned and / or existing problems in the existing method for systematically detecting defects in electrical secondary circuits, the present invention is proposed.

[0006] Therefore, the problem to be solved by the present invention is that it cannot meet the needs of complex and changeable work scenarios, the detection accuracy is low, and the overall detection process is lengthy and tedious, and the timeliness is poor.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for systematic detection of electrical secondary circuit defects, which comprises the following steps: Step 1: Ingenious construction of the adaptive function detection device: comprising the following processes: A1: Selection and configuration of the core main control unit: Select an industry-leading embedded processor with excellent floating-point computing capabilities and efficient multi-tasking capabilities, and specially open up independent partitions for storing adaptive control algorithm program codes, long-term accumulated historical electrical data, and real-time data cache areas to ensure that the data reading and writing speeds meet the system's high-frequency sampling and rapid analysis requirements, and the data reading and writing delays are controlled within 10 microseconds; A2: Layered deployment and characteristics of the sensor matrix: S1: Basic power collection layer :This layer is the key layout for obtaining the basic electrical parameters of the electrical secondary circuit. The voltage transformer is designed with an intelligent ratio switching function. Through the built-in micro-electromechanical system drive mechanism, according to the instructions of the main control unit, it can flexibly and adaptively switch between 5 ratios in the range of 1:100-1:1000, and the corresponding range seamlessly covers 0-1000V. The measurement accuracy is stably maintained at 0.1 level. Both low-voltage control signals and high-voltage side feedback can be accurately captured. The current transformer innovatively introduces an intelligent relay to control the winding turn ratio switching mechanism; S2: Environmental perception layer: integrated high-precision temperature and humidity sensors, using the SHT31 sensor chip of Switzerland's Sensirion, using the capacitive sensing principle, after internal calibration and temperature The compensation circuit is optimized. At the same time, the electromagnetic interference monitoring antenna adopts a broadband logarithmic periodic antenna design, and cooperates with a high-sensitivity RF receiving front end and a spectrum analysis module to capture the electromagnetic interference signal strength and frequency components of the 10kHz-1GHz frequency band in real time, and transmit the environmental parameters and electromagnetic interference data to the main control unit to assist in the formulation of subsequent adaptive strategies. The data transmission cycle is 1 second; A3: Deep adaptive control algorithm operation: Adaptive control logic is built based on the deep fusion algorithm framework of fuzzy logic and artificial neural network. The fuzzy logic part predefines 20 sets of clear and clear rule sets. With simple and intuitive rules, it can quickly adjust the detection parameters for common working conditions within 10 milliseconds and preliminarily adapt to environmental electrical changes; Step 2: New Deep integration of sensors and cutting-edge detection technologies: including the following processes: B1: Principles and applications of precise monitoring by optical fiber sensors: Optical fiber sensors are precisely embedded in "hot spots" where faults frequently occur, such as cable joints, busbar connection points, and relay contacts in secondary circuits. Optical fiber temperature sensors cleverly integrate the principles of Raman scattering and Brillouin scattering. Raman scattering focuses on measuring the temperature of local points, while Brillouin scattering is used for long-distance distributed temperature monitoring. The two complement each other. B2: Terahertz detection system analyzes insulation defects: When the terahertz detection subsystem is started, an ultrashort pulse laser is generated by a femtosecond laser, which generates a terahertz wave with a specific frequency and stable power through electro-optical modulation, and is precisely focused on the surface of the secondary circuit insulation material through collimation and focusing optical components.B3: Infrared thermal imaging module locks abnormal heating: The infrared thermal imaging module uses infrared detectors to sense the thermal radiation of each component of the secondary circuit based on the Stefan-Boltzmann law, and "cruise" the entire circuit area at a preset period of 10 times per minute. Combined with the image positioning function, the precise location of abnormal heating is locked, and multi-dimensional cross-verification with optical fiber temperature and terahertz detection data is carried out to improve the accuracy and reliability of fault judgment. The time required to push the alarm information to the central processing unit is less than 500 milliseconds; Step 3: Robust establishment and efficient collaborative operation of distributed detection system: Including the following processes: C1: Modular detection unit design details and function realization: The modular detection unit adopts a "plug-in" hardware architecture, and the internal circuit board design follows the standardized electrical and mechanical interface specifications to adapt to the access requirements of protection devices of different brands and models. The internal microprocessor uses a low-power ARM core and integrates a real-time operating system to independently and efficiently control data acquisition tasks, preliminary filtering, feature extraction and communication transmission. The synchronization error between data acquisition and transmission is less than 1 millisecond; C2: None Line communication adaptation and protocol guarantee: The communication layer adapts multi-protocol wireless communication modules for different scenarios, follows a custom lightweight communication protocol, encapsulates the unit ID, timestamp, and data type in the data packet header, and attaches a cyclic redundancy check code at the end to ensure reliable, complete, and orderly data transmission, and the packet loss rate is controlled below 0.1%; C3: Central processing unit overall analysis and fault diagnosis process: The central processing unit is built on the cloud computing platform architecture, and uses elastic computing resources to expand computing power. It summarizes the data of the global distributed detection units at a frequency of 10 times per second. First, use big data statistical analysis tools to quickly calculate the statistical characteristic values ​​of the mean, variance, trend slope, etc. of each electrical parameter, and compare and screen abnormal data with the preset normal threshold interval. With the help of the fault diagnosis expert system, the root cause of the fault is accurately anchored, and finally a detailed inspection report with pictures and texts is generated. With the help of 3D modeling software, a schematic diagram of the fault location is drawn, the fault evolution process is sorted out, and the maintenance priority is evaluated, providing all-round and accurate guidance for operation and maintenance repairs. The report generation time is less than 5 minutes. ;

[0008] As a preferred solution of the method for systematically detecting defects in electrical secondary circuits of the present invention, the A1 is equipped with a large-capacity storage medium, which is a combination of a high-speed solid-state hard disk with a capacity of 512GB and an externally expanded 8GB DDR4 memory.

[0009] As a preferred solution of the systematic detection method for electrical secondary circuit defects described in the present invention, wherein: in S1, the current current range is estimated based on the statistical analysis of the big data of the previous operating current of the circuit, and the number of primary and secondary winding connection turns is changed quickly within 20 milliseconds by means of the relay. The range is flexibly adapted to the range of 0-100A, and the accuracy reaches 0.2 level. The collected analog voltage and current signals are digitized in real time by a high-precision analog-to-digital converter and then transmitted to the main control unit at a high speed of 1Mbps for analysis and processing.

[0010] As a preferred solution of the systematic detection method for electrical secondary circuit defects described in the present invention, the temperature measurement accuracy of the SHT31 sensor chip in S2 can reach ±0.5°C, the humidity accuracy is stable at ±3%RH, and the temperature and humidity changes in the working range are continuously monitored at a frequency of 5 times per second.

[0011] As a preferred solution of the systematic detection method for electrical secondary circuit defects described in the present invention, the artificial neural network in A3 focuses on the analysis of complex and nonlinear working conditions, deeply mines the rules contained in historical data, and constructs a "portrait model" of complex working conditions.

[0012] As a preferred solution of the method for systematically detecting defects in electrical secondary circuits described in the present invention, the optical fiber current sensor in B1 utilizes the Faraday magneto-optical effect. When light in a specific polarization state passes through the optical fiber coil surrounding the current conductor, the polarization plane rotates under the action of the magnetic field. The rotation angle is linearly related to the measured current. With the help of a high-sensitivity photodetector and a signal demodulation circuit, milliampere-level precision current monitoring is achieved in a wide range of 0-1000A. In addition, due to the natural electromagnetic shielding characteristics of the optical fiber material, it is immune to strong electromagnetic interference, stably outputs precise current values, and provides real-time feedback on the loop current status. The data update cycle is 10 milliseconds.

[0013] As a preferred solution of the systematic detection method for electrical secondary circuit defects described in the present invention, when the terahertz wave in B2 penetrates the insulating layer and encounters internal microcracks or moisture-induced stratification defects, the reflection, scattering and transmission characteristics change due to the sudden change in the dielectric constant. The echo signal is collected by a high-sensitivity terahertz detector array, and is processed by fast Fourier transform and inverse scattering imaging algorithm to reconstruct a 3D image of the internal microstructure of the insulation, intuitively display the health status of the insulation, and warn of the risk of insulation degradation in advance. The imaging time for a single scan is 1 minute.

[0014] As a preferred solution of the systematic detection method for electrical secondary circuit defects described in the present invention, the infrared thermal image collected in B3 is processed by image preprocessing, temperature calibration and gradient analysis algorithm, focusing on the temperature difference between adjacent areas. Once the temperature difference exceeds the threshold of 10°C, an alarm signal is immediately triggered.

[0015] As a preferred solution of the systematic detection method of electrical secondary circuit defects described in the present invention, the Wi-Fi6 module is used in the indoor short-distance area of ​​C2 with high-speed data interaction requirements, and its high bandwidth and low latency characteristics ensure the rapid transmission of massive data; the LoRaWAN module is used in outdoor long-distance and complex terrain scenarios, and its excellent penetration ability and low power consumption characteristics ensure the stable return of data from remote secondary circuit detection units.

[0016] As a preferred solution of the method for systematically detecting defects in electrical secondary circuits described in the present invention, once an abnormality is found in C3, an instruction is immediately sent to the adaptive detection device to trigger "secondary focusing", and the detection parameters are adjusted to dig deep into the root cause of the fault. The instruction transmission delay is less than 10 milliseconds. At the same time, multiple units are dispatched to work together to dig deep into the fault chain based on the fault association logic.

[0017] The beneficial effects of the present invention are as follows: in terms of detection accuracy, with the help of the integration of multiple high-precision sensors and advanced detection technology, the insulation detection accuracy reaches the millimeter level, the electrical parameter error is reduced by 80%, it can capture milliampere-level current changes, and accurately identify potential faults. In terms of adaptability to working conditions, the adaptive mechanism covers electrical and environmental factors, and intelligently adjusts parameters under -40°C to 70°C, humidity 10%-95% and 0.05-15 times the rated load fluctuation, and the false alarm rate is reduced from 20% to less than 2%. In terms of operation and maintenance efficiency, the distributed architecture is combined with intelligent diagnosis to shorten the detection cycle to 10 minutes / time, and reduce fault location from 4 hours to 30 minutes, greatly improving the emergency repair time and power supply reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0019] Figure 1 The figure is an overall flow chart of a systematic detection method for electrical secondary circuit defects.

[0020] Figure 2 It is a time sequence diagram of command transmission and response of the systematic detection method of electrical secondary circuit defects.

[0021] Figure 3 A fault-related logic mind map for a systematic detection method for electrical secondary circuit defects.

[0022] Figure 4 A multi-unit collaborative operation flow chart for a systematic detection method for electrical secondary circuit defects. DETAILED DESCRIPTION

[0023] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0024] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0025] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0026] Example 1

[0027] Reference Figure 1-Figure 4 , which is the first embodiment of the present invention, and provides a method for systematically detecting defects in an electrical secondary circuit. The method for systematically detecting defects in an electrical secondary circuit comprises the following steps:

[0028] Step 1: Exquisite construction of adaptive function detection device: including the following processes: A1: Selection and configuration of core main control unit: select an industry-leading embedded processor with excellent floating-point computing capability and efficient multi-tasking processing capability, and open up independent partitions to store adaptive control algorithm program code, long-term accumulated historical electrical data and real-time data cache area, to ensure that the data reading and writing speed meets the system's high-frequency sampling and rapid analysis requirements, and the data reading and writing delay is controlled within 10 microseconds, with large-capacity storage media, using a high-speed solid-state hard drive with a capacity of 512GB and an externally expanded 8GB DDR4 memory combination form; A2: Sensor matrix hierarchical deployment and characteristics: S1: Basic power collection layer: This layer is the key layout for obtaining the basic electrical parameters of the electrical secondary circuit. The voltage transformer is designed with an intelligent ratio switching function. Through the built-in micro-electromechanical system drive mechanism, according to the instructions of the main control unit, it can flexibly and adaptively switch between 5 ratios in the range of 1:100-1:1000, and the corresponding range seamlessly covers 0-1000V. The measurement accuracy is stably maintained at 0.1 level. Both low-voltage control signals and high-voltage side feedback can be accurately The current transformer innovatively introduces an intelligent relay to control the winding turns ratio switching mechanism. The current range is estimated based on the statistical analysis of the previous current data of the loop. The relay quickly changes the number of turns of the primary and secondary windings within 20 milliseconds. The range is flexibly adapted to the range of 0-100A, with an accuracy of 0.2. The collected analog voltage and current signals are digitized by a high-precision analog-to-digital converter in real time and transmitted to the main control unit at a high speed of 1Mbps for analysis and processing; S2: Environmental perception layer: integrated with high-precision temperature and humidity sensors, using Rui The SHT31 sensor chip of Shisheng Sirui Company has a temperature measurement accuracy of up to ±0.5℃ and a humidity accuracy of ±3%RH. It continuously monitors the temperature and humidity changes in the working range at a frequency of 5 times per second. It uses the capacitive sensing principle and is optimized through internal calibration and temperature compensation circuit. At the same time, the electromagnetic interference monitoring antenna adopts a broadband logarithmic periodic antenna design, and cooperates with a high-sensitivity RF receiving front end and a spectrum analysis module to capture the electromagnetic interference signal strength and frequency components in the 10kHz-1GHz frequency band in real time, and transmits the environmental parameters and electromagnetic interference data to the main control unit to assist in the formulation of subsequent adaptive strategies. The data transmission cycle is 1 second; A3: Deep adaptive control algorithm operation: Adaptive control logic is built based on the deep fusion algorithm framework of fuzzy logic and artificial neural network. The fuzzy logic part predefines 20 sets of clear and clear rule sets. With simple and intuitive rules, it can quickly adjust the detection parameters of common working conditions within 10 milliseconds and preliminarily adapt to environmental electrical changes. The artificial neural network focuses on the analysis of complex and nonlinear working conditions, deeply mines the laws contained in historical data, and builds a "portrait model" of complex working conditions;Step 2: Deep integration of new sensors and cutting-edge detection technologies: including the following processes: B1: Principle and application of precise monitoring of optical fiber sensors: Optical fiber sensors are precisely embedded in the "hot spots" where faults frequently occur at secondary circuit cable joints, busbar connection points, and relay contacts. Optical fiber temperature sensors cleverly integrate the principles of Raman scattering and Brillouin scattering. Raman scattering focuses on measuring local point temperature, and Brillouin scattering is used for long-distance distributed temperature monitoring. The two complement each other. Optical fiber current sensors use the Faraday magneto-optical effect. When light in a specific polarization state passes through the optical fiber coil surrounding the current conductor, the polarization plane rotates under the action of the magnetic field. The rotation angle is linearly related to the current being measured. With the help of high-sensitivity light detectors and signal demodulation circuits, at 0 -1000A wide range realizes milliampere-level precision current monitoring, and with the natural electromagnetic shielding characteristics of optical fiber material, it is immune to strong electromagnetic interference, stably outputs accurate current values, and provides real-time feedback on loop current status. The data update cycle is 10 milliseconds; B2: Terahertz detection system analyzes insulation defects: When the terahertz detection subsystem is started, the femtosecond laser generates ultra-short pulse lasers, which are electro-optically modulated to generate terahertz waves with specific frequency and stable power. The terahertz waves are precisely focused on the surface of the secondary circuit insulation material through collimation and focusing optical components. When the terahertz waves penetrate the insulation layer, when they encounter internal microcracks and moisture-induced stratification defects, the dielectric constant mutation causes changes in reflection, scattering and transmission characteristics. The high-sensitivity terahertz detector array is used to detect insulation defects. Collect echo signals, process them through fast Fourier transform and inverse scattering imaging algorithms, reconstruct 3D images of the internal microstructure of the insulation, intuitively display the health of the insulation, and warn of the risk of insulation degradation in advance. The imaging time for a single scan is 1 minute; B3: Infrared thermal imaging module locks abnormal heating: The infrared thermal imaging module uses infrared detectors to sense the thermal radiation of each component of the secondary circuit based on the Stefan-Boltzmann law, and "cruise" the entire circuit at a preset period of 10 times per minute. Combined with the image positioning function, the precise location of abnormal heating is locked, and multi-dimensional cross-verification with optical fiber temperature and terahertz detection data is carried out to improve the accuracy and reliability of fault judgment. The alarm information is pushed to the central processing unit in less than 500 milliseconds, and the collected infrared The external thermal image is processed by image preprocessing, temperature calibration and gradient analysis algorithm, focusing on the temperature difference between adjacent areas. Once the temperature difference exceeds the 10℃ threshold, the alarm signal is triggered immediately; Step 3: Robust establishment and efficient collaborative operation of the distributed detection system: including the following processes: C1: Modular detection unit design details and function implementation: The modular detection unit adopts a "plug-in" hardware architecture, and the internal circuit board design follows the standardized electrical and mechanical interface specifications to adapt to the access requirements of protection devices of different brands and models. The internal microprocessor uses a low-power ARM core and integrates a real-time operating system to independently and efficiently control data acquisition tasks, preliminary filtering, feature extraction and communication transmission. The synchronization error between data acquisition and transmission is less than 1 millisecond;C2: Wireless communication adaptation and protocol guarantee: The communication layer adapts multi-protocol wireless communication modules for different scenarios, follows the custom lightweight communication protocol, and encapsulates the unit ID, timestamp, and data type in the data packet header, with a cyclic redundancy check code at the end to ensure reliable, complete, and orderly data transmission. The packet loss rate is controlled below 0.1%. Wi-Fi6 modules are used in indoor close-range areas with high-speed data interaction requirements. With its high bandwidth and low latency characteristics, it ensures the rapid transmission of massive data; LoRaWAN modules are used in outdoor long-distance and complex terrain scenarios. With its excellent penetration ability and low power consumption characteristics, it ensures the stable return of data from remote secondary circuit detection units; C3: Central processing unit overall analysis and fault diagnosis process: The central processing unit is built on the cloud computing platform architecture, with the help of Elastic computing resources expand computing power, and aggregate the data of distributed detection units across the entire domain at a frequency of 10 times per second. First, use big data statistical analysis tools to quickly calculate the statistical characteristic values ​​of the mean, variance, trend slope, etc. of each electrical parameter, and compare and screen abnormal data with the preset normal threshold interval. With the help of the fault diagnosis expert system, the root cause of the fault is accurately anchored. Once an abnormality is found, an instruction is immediately sent to the adaptive detection device to trigger "secondary focus", adjust the detection parameters to dig deep into the root cause of the fault, and the instruction transmission delay is less than 10 milliseconds. At the same time, multiple units are dispatched to work together, and the fault chain is dug deep according to the fault association logic. Finally, a detailed inspection report with pictures and texts is generated. With the help of 3D modeling software, a schematic diagram of the fault location is drawn, the fault evolution process is sorted out, and the maintenance priority is evaluated, providing all-round and accurate guidance for operation and maintenance repairs. The report generation time is less than 5 minutes. ;

[0029] Example 2

[0030] Reference Figure 1-Figure 4 , which is the second embodiment of the present invention, and this embodiment is based on the previous embodiment.

[0031] Substation indoor secondary circuit detection

[0032] Scene Setting

[0033] In the indoor secondary equipment area of ​​a city substation, there are multiple relay protection devices, measurement and control devices, and a complex secondary cable connection network. The ambient temperature is controlled at 20℃-25℃, and the humidity is maintained at 40%-60%. The electromagnetic interference mainly comes from the stray electromagnetic field generated by the normal operating primary equipment and communication equipment in the station. The intensity is within the conventional range (the average electric field strength is about 5V / m, and the magnetic field strength is about 0.1A / m). The secondary circuit load changes dynamically between 30%-70% of the rated load with the power allocation in the station.

[0034] Detection system deployment and operation

[0035] Installation of the adaptive function detection device: Place the core main control unit (TI TMS320C6678) in a dedicated slot in the secondary equipment control cabinet to ensure good heat dissipation and electrical connection. The voltage and current transformers of the basic power collection layer are accurately connected to each phase line and neutral point of the secondary circuit, tightly fitting the cables to ensure effective signal acquisition. The temperature and humidity sensors and electromagnetic interference monitoring antennas of the environmental perception layer are reasonably distributed in different corners of the control cabinet to monitor the overall environment. After the device is started, the adaptive control algorithm and historical data are quickly loaded from the storage medium, the detection parameters are initialized, and the electrical parameter acquisition is started at the preset 5kHz sampling frequency.

[0036] New sensor layout: Fiber optic sensors are carefully installed at the cable joints, and the optical fiber surrounds the cable conductor to ensure that the magneto-optical effect accurately senses the current; at the busbar connection point, the fiber optic temperature sensor is firmly attached to monitor the temperature in real time. The terahertz detection equipment regularly (once every 2 hours) scans and detects key insulation parts (such as the secondary insulation of the wall bushing and the insulation shell of the relay), and uses the robot arm to assist in positioning to ensure the accurate incidence of the wave. The infrared thermal imaging module is suspended above the equipment area, "patrolling" the surface of the circuit equipment in all directions at a frequency of 10 times per minute.

[0037] Distributed detection unit configuration: Each modular detection unit is installed in a corresponding adjacent position according to the type of protection device (such as line protection, main transformer protection), conveniently fixed by DIN rail, and closely connected to the protection device with the help of an electrical interface that complies with the IEC 61850 standard. The internal microprocessor operates efficiently, collects data and transmits it to the central processing unit (deployed in the monitoring host on the site, relying on Alibaba Cloud Elastic Computing Service) in real time through the Wi-Fi6 (Qualcomm QCA6390) module according to a custom protocol. The transmission packet loss rate is stable below 0.1%, ensuring smooth data flow.

[0038] Fault Detection and Response Process

[0039] After a power load adjustment operation, the load on the secondary circuit of a certain line suddenly dropped to about 20% of the rated value. At this time, the neural network algorithm of the adaptive detection device responded quickly (within 20 milliseconds), increased the current sampling frequency to 2kHz, narrowed the voltage range to 50% of the original, and captured the weak harmonic distortion of the current (the third harmonic content increased by 10% compared with normal). At the same time, the optical fiber current sensor synchronously monitored the slight abnormality of the current with milliampere accuracy, and the two data were cross-confirmed. After the central processing unit received the abnormal data (within 1 second), it dispatched the corresponding distributed detection unit to dig deep into the related data. Combined with the terahertz scanning insulation, there was no abnormality, and the infrared thermal imaging showed that the temperature of the corresponding relay shell increased by 8°C (not reaching the alarm threshold). After the fault diagnosis expert system judged, it was locked in as the performance degradation of the current sampling board component in the line protection device, and a high-priority maintenance report was generated (including 3D fault location indication accurate to the millimeter level, and the fault evolution curve showing the change process of current harmonics) and pushed to the mobile terminal of the operation and maintenance personnel. The operation and maintenance personnel replaced the board within 30 minutes based on the report to restore the normal operation of the circuit.

[0040] Example 3

[0041] Reference Figure 1-Figure 4 , which is the third embodiment of the present invention, and is based on the first two embodiments.

[0042] Outdoor high voltage tower secondary circuit detection

[0043] Scene Setting

[0044] At the bottom of the tower of a high-voltage transmission line in a certain mountainous area, the secondary circuit is responsible for lightning protection of the tower, monitoring of insulator leakage current and remote monitoring of line status. The environmental conditions are harsh, with temperatures fluctuating greatly between -10°C and 40°C, and humidity often between 60% and 90%. Especially in rainy and foggy weather, the humidity is close to saturation. Electromagnetic interference is affected by lightning and surrounding radio stations, and the intensity fluctuates greatly (the electric field strength can reach up to 50V / m, and the magnetic field strength is 1A / m). The circuit load frequently changes between 10% and 80% of the rated load due to day and night light and climate, causing the equipment to start and stop.

[0045] Detection system deployment and operation

[0046] Placement of the adaptive function detection device: The device is encapsulated in a waterproof, dustproof, and anti-electromagnetic interference chassis, fastened next to the secondary equipment box at the bottom of the tower, and each sensor is properly connected to the secondary circuit. Considering the changeable outdoor environment, the device strengthens the frequency of environmental perception, the temperature and humidity sensors sample 8 times per second, and the electromagnetic interference monitoring is always on. According to weather data (access to the local weather station data interface) and real-time environmental perception, the detection parameters are flexibly adjusted, and the redundant range of electrical parameter measurement is appropriately increased in severe weather.

[0047] New sensor layout: Fiber optic sensors are carefully deployed at key locations such as the secondary connection of the lightning protection grounding lead and the secondary cable joints of the insulator to resist electromagnetic interference and accurately monitor the current temperature; the terahertz detection system conducts a deep scan of outdoor insulation equipment (such as the secondary insulation wrapping layer of the insulator and the outdoor secondary junction box) once a week in clear weather, using a portable bracket for precise positioning to analyze the long-term environmental erosion of the insulation. The infrared thermal imaging module combines solar power supply with low-power standby mode, and starts every 30 minutes to inspect the heating status of the circuit.

[0048] Operation of distributed detection units: The modular detection units adapted to outdoor conditions adopt a waterproof and sealed design and a high protection level (IP65). With the help of the LoRaWAN (SX1308) module, they penetrate mountains and forests and communicate over long distances. The detection data scattered throughout the tower (such as insulator monitoring points at different heights and lightning protection monitoring terminals) are stably transmitted back to the central processing unit (located at the cloud computing platform of the substation monitoring center at the foot of the mountain) across several kilometers. Even in extreme weather such as heavy rain and strong winds, the communication packet loss rate is controlled within 0.1% to ensure data integrity.

[0049] Fault Detection and Response Process

[0050] After a week of continuous rain and fog, the humidity exceeded 80% for a long time and the temperature dropped to about 5°C. The adaptive detection device increased the insulation resistance measurement excitation voltage and frequency according to the fuzzy logic rules (humidity exceeded 80% and temperature was below 10°C), and found that the insulation resistance of a certain insulator secondary circuit was 60% lower than the normal value, triggering an alarm. At the same time, the terahertz scan showed that there were 0.2mm micro cracks inside the secondary insulation of the insulator, with a depth of 0.3mm. The infrared thermal imaging captured that the temperature of the corresponding part was 12°C higher than the surrounding area. The central processing unit coordinated with multiple distributed detection units to trace the related data. The expert system diagnosed that the secondary insulation of the insulator was damp, and the micro cracks caused partial discharge and heating failures. An emergency maintenance report was generated (including a clear 3D fault diagram marking the specific location of the tower and a fault development stage chart) and pushed it to the operation and maintenance team. The operation and maintenance personnel completed the insulator replacement within 2 hours with the help of a helicopter live operation to ensure the safe and stable operation of the secondary circuit of the transmission line.

[0051] 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 method for systematically detecting defects in electrical secondary circuits, characterized in that: The following steps are involved: Step 1: The adaptive function detection device is delicately constructed: including the following processes: A1: Selection and configuration of the core main control unit: Select an industry-leading embedded processor with excellent floating-point computing capabilities and efficient multi-tasking capabilities, and set up an independent partition to store adaptive control algorithm program codes, long-term accumulated historical electrical data, and real-time data cache areas to ensure that the data reading and writing speeds meet the system's high-frequency sampling and rapid analysis requirements, and the data reading and writing delay is controlled within 10 microseconds; A2: Sensor matrix hierarchical deployment and characteristics: S1: Basic power collection layer: This layer is the key layout for obtaining the basic electrical parameters of the electrical secondary circuit. The voltage transformer is designed with an intelligent ratio switching function. Through the built-in micro-electromechanical system drive mechanism, according to the instructions of the main control unit, it can flexibly and adaptively switch between 5 ratios in the range of 1:100-1:1000, and the corresponding range seamlessly covers 0-1000V. The measurement accuracy is stably maintained at 0.1 level. Both low-voltage control signals and high-voltage side feedback can be accurately captured. The current transformer innovatively introduces an intelligent relay to control the winding turn ratio switching mechanism; S2: Environmental perception layer: integrated high-precision temperature and humidity sensor, using the SHT31 sensor chip of Switzerland's Sensirion, using the capacitive sensing principle, after internal calibration and temperature compensation circuit optimization, at the same time, the electromagnetic interference monitoring antenna adopts a broadband logarithmic periodic antenna design, with a high-sensitivity RF receiving front end and spectrum analysis module, to capture the electromagnetic interference signal strength and frequency components in the 10kHz-1GHz frequency band in real time, and transmit the environmental parameters and electromagnetic interference data to the main control unit to assist in the subsequent adaptive strategy formulation. The data transmission cycle is 1 second; A3: Deep adaptive control algorithm operation: Adaptive control logic is built based on the deep fusion algorithm framework of fuzzy logic and artificial neural network. The fuzzy logic part predefines 20 sets of clear and specific rule sets. With simple and intuitive rules, the detection parameters of common working conditions can be quickly adjusted within 10 milliseconds to preliminarily adapt to environmental electrical changes. Step 2: Deep integration of new sensors and cutting-edge detection technologies: including the following processes: B1: Principle and application of precise monitoring by optical fiber sensors: Optical fiber sensors are precisely embedded in the "hot spots" where faults frequently occur, such as secondary circuit cable joints, busbar connection points, and relay contacts. Optical fiber temperature sensors cleverly integrate the principles of Raman scattering and Brillouin scattering. Raman scattering focuses on measuring the temperature of local points, while Brillouin scattering is used for long-distance distributed temperature monitoring. The two complement each other. B2: Terahertz detection system analyzes insulation defects: When the terahertz detection subsystem is started, the femtosecond laser generates ultra-short pulse lasers, which are electro-optically modulated to generate terahertz waves with specific frequency and stable power, and are precisely focused on the surface of the secondary circuit insulation material through collimation and focusing optical components; B3: Infrared thermal imaging module locks abnormal heating: The infrared thermal imaging module uses infrared detectors to sense the thermal radiation of each component of the secondary circuit based on the Stefan-Boltzmann law, and "cruise" the entire circuit periodically 10 times per minute. Combined with the image positioning function, it locks the exact location of abnormal heating, and cross-checks with the fiber temperature and terahertz detection data in multiple dimensions. It takes less than 500 milliseconds to push the alarm information to the central processing unit; Step 3: Robust construction and efficient collaborative operation of distributed detection system: including the following processes: C1: Modular detection unit design details and function realization: The modular detection unit adopts a "plug-in" hardware architecture. The internal circuit board design follows the standardized electrical and mechanical interface specifications to adapt to the access requirements of protection devices of different brands and models. The internal microprocessor uses a low-power ARM core and integrates a real-time operating system to independently and efficiently control data collection tasks, preliminary filtering, feature extraction and communication transmission. The synchronization error between data collection and transmission is less than 1 millisecond; C2: Wireless communication adaptation and protocol assurance: The communication layer adapts multi-protocol wireless communication modules for different scenarios, follows a custom lightweight communication protocol, and encapsulates the unit ID, timestamp, and data type in the data packet header, with a cyclic redundancy check code at the end to ensure reliable, complete, and orderly data transmission, with a data packet transmission loss rate controlled below 0.1%; C3: Central processing unit coordinated analysis and fault diagnosis process: The central processing unit is built on the cloud computing platform architecture, with the help of elastic computing resources to expand computing power, and summarizes the data of distributed detection units across the entire domain at a frequency of 10 times per second. First, use big data statistical analysis tools to quickly calculate the statistical characteristic values ​​of each electrical parameter, such as the mean, variance, and trend slope, and compare them with the preset normal threshold range to screen abnormal data. With the help of the fault diagnosis expert system, the root cause of the fault is accurately anchored, and finally a detailed inspection report with pictures and texts is generated. With the help of 3D modeling software, a schematic diagram of the fault location is drawn, the fault evolution process is sorted out, and the maintenance priority is evaluated, providing all-round and accurate guidance for operation and maintenance repairs. The report generation time is less than 5 minutes.

2. A method for systematically detecting defects in electrical secondary circuits according to claim 1, characterized in that: The A1 is equipped with a large-capacity storage medium, which is a combination of a high-speed solid-state hard drive with a capacity of 512GB and an externally expanded 8GB DDR4 memory.

3. A method for systematically detecting defects in electrical secondary circuits according to claim 1, characterized in that: In the S1, the current range is estimated based on the statistical analysis of the previous current big data of the loop operation, and the number of turns of the primary and secondary windings is changed quickly within 20 milliseconds by means of relays. The range is flexibly adapted to the range of 0-100A, with an accuracy of 0.

2. The collected analog voltage and current signals are digitized in real time by a high-precision analog-to-digital converter and transmitted to the main control unit at a high speed of 1Mbps for analysis and processing.

4. A method for systematically detecting defects in electrical secondary circuits according to claim 1, characterized in that: The temperature measurement accuracy of the SHT31 sensor chip in S2 can reach ±0.5°C, and the humidity accuracy is stable at ±3%RH. It continuously monitors the temperature and humidity changes in the working range at a frequency of 5 times per second.

5. A method for systematically detecting defects in electrical secondary circuits according to claim 1, characterized in that: The artificial neural network in A3 focuses on analyzing complex and nonlinear working conditions, deeply mining the patterns contained in historical data, and constructing a "portrait model" of complex working conditions.

6. A method for systematically detecting defects in electrical secondary circuits according to claim 1, characterized in that: The fiber optic current sensor in B1 utilizes the Faraday magneto-optical effect. When light in a specific polarization state passes through the fiber optic coil surrounding the current conductor, the polarization plane rotates due to the action of the magnetic field. The rotation angle is linearly related to the measured current. With the help of a high-sensitivity light detector and a signal demodulation circuit, milliampere-level precision current monitoring is achieved in a wide range of 0-1000A. In addition, due to the natural electromagnetic shielding properties of the optical fiber material, it is immune to strong electromagnetic interference, stably outputs precise current values, and provides real-time feedback on the loop current status. The data update cycle is 10 milliseconds.

7. A method for systematically detecting defects in electrical secondary circuits according to claim 1, characterized in that: When the terahertz wave in B2 penetrates the insulation layer and encounters internal microcracks or moisture-induced stratification defects, the dielectric constant mutation causes changes in reflection, scattering and transmission characteristics. The echo signal is collected using a high-sensitivity terahertz detector array and processed through a fast Fourier transform and inverse scattering imaging algorithm to reconstruct a 3D image of the internal microstructure of the insulation, intuitively displaying the health status of the insulation and providing early warning of the risk of insulation degradation. The imaging time for a single scan is 1 minute.

8. A method for systematically detecting defects in electrical secondary circuits according to claim 1, characterized in that: The infrared thermal image collected in B3 is processed by image preprocessing, temperature calibration and gradient analysis algorithm, focusing on the temperature difference between adjacent areas. Once the temperature difference exceeds the threshold of 10°C, an alarm signal is immediately triggered.

9. A method for systematically detecting defects in electrical secondary circuits according to claim 1, characterized in that: The C2 uses Wi-Fi 6 modules in indoor short-distance areas with high-speed data interaction requirements, which ensure the rapid transmission of massive data with its high bandwidth and low latency characteristics; LoRaWAN modules are used in outdoor long-distance and complex terrain scenarios, which ensure stable data return from remote secondary circuit detection units with its excellent penetration ability and low power consumption characteristics.

10. A method for systematically detecting defects in electrical secondary circuits according to claim 1, characterized in that: Once an abnormality is found in the C3, a command is immediately sent to the adaptive detection device to trigger "secondary focusing", and the detection parameters are adjusted to dig deep into the root cause of the fault. The command transmission delay is less than 10 milliseconds. At the same time, multiple units are dispatched to work together to dig deep into the fault chain based on the fault correlation logic.

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