A system and method for reducing the failure rate of power distribution network automation terminals

Abstract

The application belongs to the technical field of power distribution network automation, and discloses a system and method for reducing the failure rate of a power distribution network automation terminal, wherein the system comprises a master control, a telemetry module, a remote signaling module, a remote control module, an environment monitoring module, a fault self-diagnosis module, an intelligent protection module, a power supply voltage stabilization protection module, a fault early warning module and a storage module; the environment monitoring module collects temperature, humidity, dust concentration and voltage and current; the fault self-diagnosis module detects software and hardware and communication links, and repairs slight faults; the intelligent protection module controls the temperature three-stage speed regulation heat dissipation and dustproof sealing according to the dust concentration; the power supply voltage stabilization protection module realizes surge absorption, voltage stabilization and over / under voltage protection; and the fault early warning module realizes three-stage early warning and linkage with the power distribution network master station; the method realizes multi-parameter cooperative monitoring, fault self-diagnosis and self-repair, feedback type environment protection, power supply whole-process protection, fault grading early warning, remote operation and maintenance linkage and whole-process closed-loop management and control; the application can reduce the terminal failure rate, improve the self-repair of slight faults and greatly reduce the operation and maintenance cost.

Description

Technical Field

[0001] This invention relates to the field of power distribution network automation technology, and in particular to a system and method for reducing the failure rate of power distribution network automation terminals. Background Technology

[0002] With the advancement of intelligent power system construction, distribution network automation has become a core means to improve the management level and power supply reliability of distribution networks. As the field execution unit of the distribution network automation system, the operational stability of the distribution network automation terminal directly determines the implementation effect of distribution network automation. At present, distribution network automation terminals are widely deployed in outdoor pole-mounted, open-air switch stations and other scenarios, facing complex operating environments such as high temperature, high humidity, dust, lightning strikes, and large fluctuations in power supply voltage. At the same time, the internal hardware integration of the terminal is constantly increasing, the heat dissipation pressure is increasing, and most of the existing terminals are traditional fixed designs, lacking targeted environmental adaptation and fault early warning mechanisms.

[0003] In recent years, the operation and maintenance units of distribution networks have only monitored the operation of terminals remotely in the background. When the background detects abnormal data, the terminal has already failed. This is post-event monitoring and cannot prevent failures in advance. Moreover, the heat dissipation of existing terminals mostly adopts natural heat dissipation and dust prevention relies on simple outer shell sealing. In high temperature and dust environments, components are prone to overheating and damage, and dust can enter and cause short circuits. This further increases the terminal failure rate and has become a key bottleneck restricting the development of distribution network automation.

[0004] In actual operation, due to the influence of complex outdoor environment, unstable power supply voltage, lack of real-time fault detection mechanism of equipment itself, and insufficient heat dissipation and dust prevention design, the terminal failure rate remains high. Frequent faults such as telemetry data distortion, remote signal interruption, and failure to execute remote control commands not only increase the manpower and material costs of distribution network operation and maintenance, but also reduce the reliability of distribution network automation system and the stability of distribution network power supply, and cannot meet the needs of intelligent operation of distribution network.

[0005] Therefore, developing a system and method to reduce the failure rate of distribution network automation terminals has become the key to solving the pain points of existing technologies. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the present invention aims to provide a system and method for reducing the failure rate of distribution network automation terminals. By integrating five major functions—environmental monitoring, fault self-diagnosis, intelligent protection, power supply stabilization, and fault early warning—it achieves comprehensive and multi-dimensional control over the entire operation process of distribution network automation terminals. It can collect terminal operating environment parameters and their own operating status in real time, perform early diagnosis and warning of potential faults, intelligently adjust protection strategies according to environmental changes, and simultaneously stabilize and surge protect the power supply voltage. This addresses the high terminal failure rate from three levels: fault prevention, process control, and early intervention, improving the stability and reliability of terminal operation, reducing distribution network operation and maintenance costs, and ensuring the normal operation of the distribution network automation system.

[0007] A system for reducing the failure rate of distribution network automation terminals includes a main control module, a telemetry module, a remote signaling module, a remote control module, an environmental monitoring module, a fault self-diagnosis module, an intelligent protection module, a power supply voltage stabilization and protection module, a fault early warning module, and a storage module.

[0008] The telemetry module, remote signaling module, remote control module, environmental monitoring module, fault self-diagnosis module, intelligent protection module, power supply voltage regulation and protection module, and storage module are all electrically connected to the main control module.

[0009] The fault early warning module is electrically connected to the main control module and is also communicatively connected to the distribution network automation master station.

[0010] The main control module is the core control module of the distribution network terminal. It receives the collected and detected data from each module and realizes the coordinated work of each module according to the preset control logic.

[0011] The telemetry module, telesignal module, and remote control module are used to realize the core functions of telemetry, telesignal, and remote control of the distribution network automation terminal.

[0012] The storage module is used to store the terminal's historical fault data, operating parameters, and preset calibration parameters.

[0013] The environmental monitoring module collects environmental parameters inside and outside the terminal, as well as voltage and current parameters at the power input terminal, in real time, and transmits the collected data to the main control module. The collected data is also transmitted to the fault early warning module as real-time operation data.

[0014] The fault self-diagnosis module performs real-time fault detection and location on the terminal's hardware units, software programs, and communication links, and feeds back the diagnostic results to the main control module. It can also perform self-repair operations on minor non-hardware damage faults that can be resolved by software reset or parameter reset, and its diagnostic data is synchronously transmitted to the fault early warning module as real-time running data.

[0015] Real-time data from the environmental monitoring module and the fault self-diagnosis module are synchronized to the fault early warning module and the storage module via the main control module, serving as the basic data for fault trend analysis;

[0016] The intelligent protection module receives control commands from the main control module, implements three-level speed regulation heat dissipation based on temperature parameters collected by the environmental monitoring module, and completes dustproof sealing regulation based on dust concentration parameters; the three-level feedback speed regulation heat dissipation includes three states: off, low-speed operation, and high-speed operation.

[0017] The power supply voltage regulation and protection module is connected in series at the terminal power supply input terminal to realize power supply surge protection, input voltage regulation and undervoltage and overvoltage protection;

[0018] The fault early warning module has a built-in fault trend analysis algorithm. It uses environmental and power supply parameters collected by the environmental monitoring module and diagnostic data from the fault self-diagnosis module as real-time operating data. Combined with historical fault data of the distribution network terminal provided by the storage module, it calculates the probability of fault occurrence of each component through data comparison and analysis, sets three-level early warning thresholds to realize fault graded early warning, and uploads the early warning information and fault location data to the distribution network automation master station.

[0019] Furthermore, the environmental monitoring module includes an internal temperature and humidity sensor inside the terminal housing, an external temperature and humidity sensor outside the terminal housing, a dust concentration sensor, and a voltage and current sensor at the power input terminal; each sensor collects parameters every 5 seconds, and all of them achieve real-time data interaction with the main control module.

[0020] Furthermore: the fault self-diagnosis module has built-in hardware detection subroutines and software detection subroutines;

[0021] The hardware detection subroutine is used to detect the on / off status and performance degradation of the terminal power module, communication module, acquisition module, and execution module; the software detection subroutine is used to detect abnormal states in terminal program operation, data transmission, and instruction execution.

[0022] Minor non-hardware damage faults that can be resolved by software reset or parameter reset include program freezes, communication link interruptions, data transmission packet loss, and slight drift of the acquisition module.

[0023] Furthermore: the intelligent protection module includes a three-level speed-regulating heat dissipation unit based on temperature feedback and a dustproof sealing unit based on dust concentration feedback;

[0024] The three-stage speed-regulating heat dissipation unit is a combination structure of a temperature-controlled three-stage speed-regulating heat dissipation fan and a heat sink. The three-stage speed regulation is based on the temperature parameters collected by the environmental monitoring module received by the main control module to achieve feedback control. Specifically, the fan is turned off when the temperature is below 25℃, the fan runs at low speed when the temperature is greater than or equal to 25℃ and less than or equal to 40℃, and the fan runs at high speed when the temperature is above 40℃.

[0025] The dustproof sealing unit includes an electric sealing baffle, a dustproof filter, and a filter differential pressure sensor, all of which are intelligently controlled by the main control module based on the parameters of the environmental monitoring module.

[0026] Furthermore: the power supply voltage stabilization and protection module is composed of a surge protector, a voltage stabilization module, and an undervoltage and overvoltage protection module connected in series;

[0027] The undervoltage and overvoltage protection module automatically cuts off the power supply to the distribution network terminal when the input voltage exceeds the terminal's rated operating range.

[0028] Furthermore: the three-level warning thresholds of the fault warning module are: light warning corresponds to a fault occurrence probability of 30%~50%, medium warning corresponds to a fault occurrence probability of 50%~80%, and severe warning corresponds to a fault occurrence probability of ≥80%. The warning mode includes terminal field warning and distribution network automation master station remote warning.

[0029] The threshold is a preset calibration parameter stored in the storage module. This parameter is derived from the 6-month trial operation data of the distribution network terminal. By comparing the failure rate of the distribution network terminal before and after the transformation, the failure probability range corresponding to each warning level is determined to ensure the accuracy and effectiveness of the warning.

[0030] Furthermore, the main control module is connected to the environmental monitoring module, fault self-diagnosis module, intelligent protection module, power supply voltage stabilization and protection module, and storage module via RS485 bus, and the fault early warning module is connected to the main control module and the distribution network automation master station via Ethernet.

[0031] Furthermore: A method for reducing the failure rate of distribution network automation terminals includes the following steps:

[0032] S1: Multi-parameter collaborative monitoring: The environmental monitoring module collects temperature and humidity, dust concentration, power supply voltage and current parameters inside and outside the distribution network terminal at a preset frequency and transmits them to the main control module in real time.

[0033] S2: Real-time self-diagnosis and self-repair of faults: The fault self-diagnosis module detects the status of terminal hardware, software and communication links in real time, locates the fault point, and automatically performs self-repair operation when it detects minor faults that are not hardware damage and can be resolved by software reset or parameter reset. When it detects medium or severe faults, it feeds back the fault information to the main control module, and the main control module stores the fault information in the storage module as historical fault data.

[0034] S3: Feedback-based environmental protection control: Based on environmental monitoring data, the main control module controls the intelligent protection module to complete the three-level speed regulation of the cooling fan and the opening and closing degree of the dustproof sealing baffle.

[0035] S4: Full Power Supply Protection: The power supply voltage regulation module absorbs and regulates the input voltage surge. In case of abnormal voltage, it triggers undervoltage or overvoltage protection to cut off the power supply.

[0036] S5: Fault Classification Early Warning: The fault early warning module calls historical fault data and preset calibration parameters from the storage module, combines them with real-time data transmitted from the environmental monitoring module and the fault self-diagnosis module to perform trend analysis, calculate the fault probability and trigger the corresponding level of early warning, and uploads the early warning and fault location data to the distribution network automation master station;

[0037] S6: Remote Operation and Maintenance Linkage: The distribution network terminal uploads its operating status, fault diagnosis, and early warning information to the master station in real time. The master station issues remote control commands to realize remote management and control of the terminal. Operation and maintenance personnel perform early intervention and precise maintenance based on early warning and location data.

[0038] Furthermore: The specific steps of the S1 multi-parameter collaborative monitoring are as follows:

[0039] S1.1: After the environmental monitoring module is started, various sensors collect raw data such as temperature and humidity inside and outside the terminal, dust concentration, and power supply voltage and current at a frequency of 5 seconds. The collected raw data is first corrected for error by a preset coefficient, and then noise is reduced by a moving average filtering algorithm to obtain accurate real-time monitoring data.

[0040] S1.2: The processed data is synchronously transmitted to the main control module and the fault early warning module (as the basis for fault analysis). At the same time, the main control module stores the filtered data to the storage module through a cyclic storage algorithm, realizing the accurate acquisition, processing, transmission and storage of multiple parameters.

[0041] The specific steps for real-time self-diagnosis and self-repair of the S2 fault are as follows:

[0042] S2.1: The fault self-diagnosis module starts hardware and software detection subroutines, and synchronously detects the status of each component of the terminal every 5 seconds with the main control module. Hardware detection compares the collected operating parameters with preset standard parameters and uses a threshold judgment algorithm to determine hardware faults. Software detection compares the collected program response time and data transmission packet loss rate with preset thresholds to determine software faults.

[0043] S2.2: When a hardware or software fault is detected, the faulty component and type are determined by fault code location technology and fed back to the main control module. For minor faults that are only software faults and have a low degree of impact, the software reset or parameter reset is automatically performed for self-repair. After repair, the fault record is updated. For hardware faults or software faults that cannot be self-repaired, the fault information is fed back to the main control module, which stores it as historical fault data and triggers the fault warning module to prepare.

[0044] The specific steps of the S3 feedback-based environmental protection control are as follows:

[0045] S3.1: The main control module receives the filtered internal temperature and dust concentration data transmitted by the environmental monitoring module, and issues control commands to the intelligent protection module according to the preset control logic. In terms of heat dissipation, a segmented PID algorithm is used to realize three-level speed regulation of the cooling fan. The fan is controlled to shut down, run at low speed or high speed according to different temperature ranges. At the same time, the PID parameters are dynamically adjusted through an adaptive correction algorithm to ensure stable temperature control.

[0046] S3.2: In terms of dust prevention, an exponential decay algorithm is adopted to intelligently adjust the opening and closing degree of the electric sealing baffle according to the dust concentration. In addition, the filter differential pressure sensor monitors the pressure inside and outside the filter in real time. When the pressure difference reaches the preset threshold, the main control module sends a filter cleaning reminder signal and transmits it to the fault early warning module as auxiliary early warning information.

[0047] Furthermore: The specific steps for the entire S4 power supply protection process are as follows:

[0048] S4.1: The power supply voltage regulation and protection module is connected in series at the power supply input terminal of the terminal and receives input voltage and current data transmitted by the environmental monitoring module in real time; when a surge occurs in the input voltage, the surge protector automatically starts to absorb the surge current and suppress voltage surges to protect the internal circuit of the terminal.

[0049] S4.2: The input voltage is regulated by a linear voltage regulation algorithm to ensure that the output voltage meets the rated operating requirements of the terminal. The input voltage is monitored in real time by a threshold judgment algorithm. Based on the preset undervoltage and overvoltage thresholds, when the input voltage exceeds the rated range, the terminal power supply is automatically cut off and a protection signal is fed back to the main control module. The main control module stores the event and triggers a fault warning.

[0050] The specific steps for the S5 fault classification and early warning system are as follows:

[0051] S5.1: The fault early warning module first calls the historical fault data in the storage module, the trial operation and actual operation records of the past 6 months and the preset calibration parameters, and combines the real-time data of the environmental monitoring module and the diagnostic data of the fault self-diagnosis module to calculate the probability of each component failure using the Bayesian estimation algorithm.

[0052] S5.2: Based on the probability range of fault occurrence, the system determines the three levels of early warning (light, medium, and heavy) and no early warning status through the early warning trigger function; different levels of early warning correspond to different on-site prompts and data upload operations. During heavy early warning, non-core terminal functions will be suspended to prevent the fault from escalating; the fault early warning module updates the fault probability calculation results every 5 seconds and dynamically adjusts the early warning level to ensure the real-time performance and accuracy of the early warning.

[0053] The specific steps for the S6 remote operation and maintenance linkage are as follows:

[0054] S6.1: The main control module integrates various data such as the operating status, faults, and early warnings of each terminal module, and uploads the data to the distribution network automation master station through RS485 bus and Ethernet. The master station analyzes the uploaded data and issues remote control commands according to the early warning level and fault conditions, which are then forwarded to the main control module through the fault early warning module.

[0055] S6.2: Based on the early warning information and fault location data from the main station, maintenance personnel formulate plans and perform precise on-site repairs. After the repairs are completed, the main control module updates the fault records and operating parameters, the fault early warning module cancels the early warning, and the terminal returns to normal. At the same time, the maintenance data is stored and used to update the relevant parameters for fault probability calculation and optimize the fuzzy PID collaborative control algorithm, thereby realizing a closed loop between maintenance and algorithm optimization and improving the accuracy of early warnings and the efficiency of module collaboration.

[0056] The present invention has the following beneficial effects:

[0057] 1. Fault detection shifts from post-incident to pre-incident and in-process: Compared with existing technologies that can only alarm after a fault occurs, this invention realizes real-time detection of terminal hardware and software through a fault self-diagnosis module. Minor faults can be repaired on their own, and potential faults can be warned in advance, reducing the occurrence of faults from the root and significantly reducing the lag in fault handling.

[0058] 2. Environmental protection changes from a single passive to a multi-dimensional intelligent proactive approach: Existing technologies only make fixed modifications to single factors such as dust prevention and heat dissipation. This invention collects multi-dimensional environmental parameters through an environmental monitoring module to realize the intelligent start-up, shutdown, and adjustment of heat dissipation and dust prevention devices. The protective measures are dynamically adapted to the environment, which not only improves the protective effect but also reduces the failure rate of the protective devices themselves.

[0059] 3. Enhance full-process protection on the power supply side and fill the gap in fault protection: Existing technologies do not consider the impact of grid voltage fluctuations and surge impacts. This invention integrates a power supply voltage stabilization and protection module to avoid terminal faults caused by voltage abnormalities from the power supply head, thus solving the protection blind spot of existing technologies.

[0060] 4. Achieve precise fault location and remote operation and maintenance, reducing operation and maintenance costs: This invention can output fault location data, and the back-end main station can realize remote monitoring and remote control. Operation and maintenance personnel do not need to blindly conduct on-site inspections. They can carry out precise and proactive operation and maintenance based on early warning information and fault location, which greatly reduces the investment of manpower and material resources and improves operation and maintenance efficiency.

[0061] 5. Modular design, strong adaptability, and low transformation cost: Each new module adopts a modular design and can be directly integrated into the existing terminal without requiring major modifications to the original structure and installation method of the terminal. It is suitable for various types of distribution network automation terminals, which facilitates large-scale promotion and application. The transformation cost is far lower than the cost of replacing a brand new terminal.

[0062] 6. Improve terminal operation stability and power supply reliability of distribution network: This invention effectively reduces the terminal failure rate from three levels: fault prevention, process control and early intervention, and greatly improves the stability of terminal operation. It avoids the failure of distribution network automation system due to terminal failure, thereby ensuring stable power supply of distribution network and improving the intelligent operation level of distribution network. Attached Figure Description

[0063] Figure 1 This is a flowchart of a method for reducing the failure rate of distribution network automation terminals. Detailed Implementation

[0064] The present invention will be further described in detail below with reference to specific embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0065] Please see the appendix Figure 1 The present invention provides an embodiment 1: a system for reducing the failure rate of distribution network automation terminals, including a main control module, a telemetry module, a remote signaling module, a remote control module, an environmental monitoring module, a fault self-diagnosis module, an intelligent protection module, a power supply voltage stabilization and protection module, a fault early warning module, and a storage module;

[0066] The telemetry module, remote signaling module, remote control module, environmental monitoring module, fault self-diagnosis module, intelligent protection module, power supply voltage regulation and protection module, and storage module are all electrically connected to the main control module;

[0067] The fault early warning module is electrically connected to the main control module and is also communicatively connected to the distribution network automation master station.

[0068] The main control module is the core control module of the distribution network terminal. It receives the collected and detected data from each module and realizes the coordinated work of each module according to the preset control logic.

[0069] The collaborative control logic employs a fuzzy PID control algorithm, expressed as follows:

[0070] ,

[0071] in It outputs control quantities to the main control module. , , These are the proportional, integral, and derivative coefficients of the PID controller. For the current control deviation, To control the deviation in the previous moment, To control the cycle;

[0072] The telemetry module, telesignal module, and remote control module are used to realize the core functions of telemetry, telesignal, and remote control of the distribution network automation terminal.

[0073] The storage module is used to store the terminal's historical fault data, operating parameters, and preset calibration parameters;

[0074] A circular storage algorithm is used. When the storage capacity reaches a threshold, the oldest historical data is automatically overwritten. The storage update function is:

[0075]

[0076] in This is the maximum capacity of the storage module. For newly collected data, For storing data;

[0077] The environmental monitoring module collects environmental parameters inside and outside the terminal, as well as voltage and current parameters at the power input terminal, in real time, and transmits the collected data to the main control module. The collected data is also transmitted to the fault early warning module as real-time operation data.

[0078] The collected data was processed using a moving average filtering algorithm for noise reduction. The filtering formula is as follows:

[0079]

[0080] in The filtered data, For the first The raw data collected this time. The filter window size is [size], and the sampling frequency is 5 seconds / sample.

[0081] The fault self-diagnosis module performs real-time fault detection and location on the terminal's hardware units, software programs, and communication links, and feeds back the diagnostic results to the main control module. It can also perform self-repair operations on minor non-hardware damage faults that can be resolved by software reset or parameter reset, and its diagnostic data is synchronously transmitted to the fault early warning module as real-time running data.

[0082] Fault diagnosis employs a fusion algorithm based on threshold determination and trend analysis. The hardware fault determination function is as follows:

[0083]

[0084] The software fault determination function is:

[0085] in , These are the results of hardware and software fault determination (1 for fault, 0 for normal). For hardware operating parameters, These are standard hardware parameters. Allowable deviations for hardware parameters For software program response time, This is the software response time threshold. For data transmission packet loss rate, This is the packet loss rate threshold;

[0086] Real-time data from the environmental monitoring module and the fault self-diagnosis module are synchronized to the fault early warning module and the storage module via the main control module, serving as the basic data for fault trend analysis;

[0087] The intelligent protection module receives control commands from the main control module, implements three-level speed regulation heat dissipation based on temperature parameters collected by the environmental monitoring module, and completes dustproof sealing regulation based on dust concentration parameters; the three-level feedback speed regulation heat dissipation includes three states: off, low-speed operation, and high-speed operation.

[0088] Temperature control uses a piecewise PID algorithm, and the fan speed control function is:

[0089]

[0090] in This refers to the fan speed. For environmental temperature monitoring, , For low-speed PID coefficients, , For high-speed PID coefficients, The maximum fan speed is given; the dustproof sealing baffle opening / closing degree control function is: ,in For the opening and closing degree of the baffle, This represents the maximum opening degree of the baffle. For dust control adjustment coefficient, Dust concentration;

[0091] The power supply voltage regulation and protection module is connected in series at the terminal power supply input end to realize power supply surge protection, input voltage regulation and undervoltage and overvoltage protection;

[0092] The voltage regulation uses a linear voltage regulation algorithm, and the output voltage control formula is as follows:

[0093]

[0094] in To output regulated voltage, Input voltage, For output current, For sampling resistor, This is the amount of compensation for voltage regulation deviation;

[0095] The over / under voltage protection judgment function is:

[0096] in To protect the trigger signal (1 for trigger protection, 0 for normal), , These are the undervoltage and overvoltage thresholds for the input voltage, respectively.

[0097] The fault early warning module has a built-in fault trend analysis algorithm. It uses the environmental and power supply parameters collected by the environmental monitoring module and the diagnostic data of the fault self-diagnosis module as real-time operating data. Combined with the historical fault data of the distribution network terminal provided by the storage module, it calculates the probability of fault occurrence of each component through data comparison and analysis, sets three-level early warning thresholds to realize fault graded early warning, and uploads the early warning information and fault location data to the distribution network automation master station.

[0098] The probability of failure occurrence is calculated using a Bayesian estimation algorithm, and the formula is as follows:

[0099]

[0100] in For real-time data The probability of failure occurrence, This represents the conditional probability of this real-time data occurring when a fault occurs. The prior probability of historical failures. The marginal probability of real-time data appearing;

[0101] The environmental monitoring module includes an internal temperature and humidity sensor inside the terminal housing, an external temperature and humidity sensor outside the terminal housing, a dust concentration sensor, and a voltage and current sensor at the power input terminal; each sensor collects parameters every 5 seconds, and all of them achieve real-time data interaction with the main control module.

[0102] The error correction formula for sensor data acquisition is: ,in For the corrected data, This is the original collected data. For calibration standard values, , For sensor calibration coefficients;

[0103] The fault self-diagnosis module has built-in hardware detection subroutines and software detection subroutines;

[0104] The hardware detection subroutine is used to detect the on / off status and performance degradation of the terminal power module, communication module, acquisition module, and execution module; the software detection subroutine is used to detect abnormal states in terminal program operation, data transmission, and instruction execution.

[0105] Minor faults that are not hardware damage and can be resolved by software reset or parameter reset include program freeze, communication link interruption, data transmission packet loss, and slight drift of the acquisition module;

[0106] The function for determining the self-repair of minor faults is:

[0107] in This is the self-repair trigger signal (1 for triggering self-repair, 0 for not triggering). This is the coefficient representing the degree of impact of the fault. The threshold is affected by minor faults;

[0108] The intelligent protection module includes a three-stage speed-regulating heat dissipation unit based on temperature feedback and a dustproof sealing unit based on dust concentration feedback;

[0109] The three-stage speed-regulating heat dissipation unit is a combination structure of a temperature-controlled three-stage speed-regulating heat dissipation fan and a heat sink. The three-stage speed regulation is based on the temperature parameters collected by the environmental monitoring module received by the main control module to achieve feedback control. Specifically, the fan is turned off when the temperature is below 25℃, the fan runs at low speed when the temperature is greater than or equal to 25℃ and less than or equal to 40℃, and the fan runs at high speed when the temperature is above 40℃.

[0110] The adaptive correction formula for the adjusted PID parameters is:

[0111] , ,

[0112] in , , This is a parameter correction amount, dynamically adjusted based on the rate of change of temperature deviation;

[0113] The dustproof sealing unit includes an electric sealing baffle, a dustproof filter, and a filter differential pressure sensor, all of which are intelligently controlled by the main control module based on the parameters of the environmental monitoring module.

[0114] The filter pressure difference determination function is: ,when At that time, the main control module sends a filter cleaning reminder signal, in which For filter pressure difference, , These are the pressures inside and outside the filter screen, This is the differential pressure threshold.

[0115] The power supply voltage stabilization and protection module consists of a surge protector, a voltage stabilizing module, and an undervoltage and overvoltage protection module connected in series.

[0116] The undervoltage and overvoltage protection module automatically cuts off the power supply to the distribution network terminal when the input voltage exceeds the terminal's rated operating range;

[0117] The formulas for setting undervoltage and overvoltage thresholds are as follows:

[0118] ,

[0119] in The rated operating voltage of the terminal. This is the allowable voltage fluctuation coefficient (range: 0.05~0.1).

[0120] The three-level warning thresholds of the fault warning module are: light warning corresponds to a fault occurrence probability of 30%~50%, medium warning corresponds to a fault occurrence probability of 50%~80%, and severe warning corresponds to a fault occurrence probability of ≥80%. The warning modes include terminal field warning and distribution network automation master station remote warning.

[0121] The threshold is a preset calibration parameter stored in the storage module. This parameter is derived from the 6-month trial operation data of the distribution network terminal. By comparing the failure rate of the distribution network terminal before and after the transformation, the failure probability range corresponding to each warning level is determined to ensure the accuracy and effectiveness of the warning.

[0122] The warning trigger function is: ,in This serves as a warning level indicator;

[0123] The main control module is connected to the environmental monitoring module, fault self-diagnosis module, intelligent protection module, power supply voltage stabilization and protection module, and storage module via RS485 bus. The fault early warning module is connected to the main control module and the distribution network automation master station via Ethernet.

[0124] Communication data uses a CRC checksum algorithm to ensure transmission accuracy. The checksum formula is: ,in For the first One byte of communication data. The number of data bytes; the fault early warning module connects to the main control module and the distribution network automation master station via Ethernet, and uses the TCP / IP protocol for data transmission. The data transmission rate control function is: ,in This is the actual transmission rate. For maximum transmission rate, This refers to the idle bandwidth of the communication link. This represents the total bandwidth of the link.

[0125] An embodiment 2 of the present invention provides a method for reducing the failure rate of distribution network automation terminals, comprising the following steps:

[0126] S1: Multi-parameter collaborative monitoring: The environmental monitoring module collects temperature and humidity, dust concentration, power supply voltage and current parameters inside and outside the distribution network terminal at a preset frequency and transmits them to the main control module in real time.

[0127] S2: Real-time self-diagnosis and self-repair of faults: The fault self-diagnosis module detects the status of terminal hardware, software and communication links in real time, locates the fault point, and automatically performs self-repair operation when it detects minor faults that are not hardware damage and can be resolved by software reset or parameter reset. When it detects medium or severe faults, it feeds back the fault information to the main control module, and the main control module stores the fault information in the storage module as historical fault data.

[0128] S3: Feedback-based environmental protection control: Based on environmental monitoring data, the main control module controls the intelligent protection module to complete the three-level speed regulation of the cooling fan and the opening and closing degree of the dustproof sealing baffle.

[0129] S4: Full Power Supply Protection: The power supply voltage regulation module absorbs and regulates the input voltage surge. In case of abnormal voltage, it triggers undervoltage or overvoltage protection to cut off the power supply.

[0130] S5: Fault Classification Early Warning: The fault early warning module calls historical fault data and preset calibration parameters from the storage module, combines them with real-time data transmitted from the environmental monitoring module and the fault self-diagnosis module to perform trend analysis, calculate the fault probability and trigger the corresponding level of early warning, and uploads the early warning and fault location data to the distribution network automation master station;

[0131] S6: Remote Operation and Maintenance Linkage: The distribution network terminal uploads the operating status, fault diagnosis, and early warning information to the master station in real time. The master station issues remote control commands to realize remote management and control of the terminal. Operation and maintenance personnel perform early intervention and precise maintenance based on early warning and location data.

[0132] The specific steps for S1 multi-parameter collaborative monitoring are as follows:

[0133] S1.1: After the environmental monitoring module is started, various sensors collect raw data such as temperature and humidity inside and outside the terminal, dust concentration, and power supply voltage and current at a frequency of 5 seconds. The collected raw data is first corrected for error by a preset coefficient, and then noise is reduced by a moving average filtering algorithm to obtain accurate real-time monitoring data.

[0134] S1.2: The processed data is synchronously transmitted to the main control module and the fault early warning module (as the basis for fault analysis). At the same time, the main control module stores the filtered data to the storage module through a cyclic storage algorithm, realizing the accurate acquisition, processing, transmission and storage of multiple parameters.

[0135] The specific steps for real-time self-diagnosis and self-repair of S2 faults are as follows:

[0136] S2.1: The fault self-diagnosis module starts hardware and software detection subroutines, and synchronously detects the status of each component of the terminal every 5 seconds with the main control module. Hardware detection compares the collected operating parameters with preset standard parameters and uses a threshold judgment algorithm to determine hardware faults. Software detection compares the collected program response time and data transmission packet loss rate with preset thresholds to determine software faults.

[0137] S2.2: When a hardware or software fault is detected, the faulty component and type are determined by fault code location technology and fed back to the main control module. For minor faults that are only software faults and have a low degree of impact, the software reset or parameter reset is automatically performed for self-repair. After repair, the fault record is updated. For hardware faults or software faults that cannot be self-repaired, the fault information is fed back to the main control module, which stores it as historical fault data and triggers the fault warning module to prepare.

[0138] The specific steps of S3 feedback-based environmental protection control are as follows:

[0139] S3.1: The main control module receives the filtered internal temperature and dust concentration data transmitted by the environmental monitoring module, and issues control commands to the intelligent protection module according to the preset control logic. In terms of heat dissipation, a segmented PID algorithm is used to realize three-level speed regulation of the cooling fan. The fan is controlled to shut down, run at low speed or high speed according to different temperature ranges. At the same time, the PID parameters are dynamically adjusted through an adaptive correction algorithm to ensure stable temperature control.

[0140] S3.2: In terms of dust prevention, an exponential decay algorithm is adopted to intelligently adjust the opening and closing degree of the electric sealing baffle according to the dust concentration; in addition, the filter differential pressure sensor monitors the pressure inside and outside the filter in real time. When the pressure difference reaches the preset threshold, the main control module sends a filter cleaning reminder signal and transmits it to the fault early warning module as auxiliary early warning information.

[0141] The specific steps for full-process protection of S4 power supply are as follows:

[0142] S4.1: The power supply voltage regulation and protection module is connected in series at the power supply input terminal of the terminal and receives input voltage and current data transmitted by the environmental monitoring module in real time; when a surge occurs in the input voltage, the surge protector automatically starts to absorb the surge current and suppress voltage surges to protect the internal circuit of the terminal.

[0143] S4.2: The input voltage is regulated by a linear voltage regulation algorithm to ensure that the output voltage meets the rated operating requirements of the terminal. The input voltage is monitored in real time by a threshold judgment algorithm. Based on the preset undervoltage and overvoltage thresholds, when the input voltage exceeds the rated range, the terminal power supply is automatically cut off and a protection signal is fed back to the main control module. The main control module stores the event and triggers a fault warning.

[0144] The specific steps for S5 fault classification and early warning are as follows:

[0145] S5.1: The fault early warning module first calls the historical fault data in the storage module, the trial operation and actual operation records of the past 6 months and the preset calibration parameters, and combines the real-time data of the environmental monitoring module and the diagnostic data of the fault self-diagnosis module to calculate the probability of each component failure using the Bayesian estimation algorithm.

[0146] S5.2: Based on the probability range of fault occurrence, the system determines the three levels of early warning (light, medium, and heavy) and no early warning status through the early warning trigger function; different levels of early warning correspond to different on-site prompts and data upload operations. During heavy early warning, non-core terminal functions will be suspended to prevent the fault from escalating; the fault early warning module updates the fault probability calculation results every 5 seconds and dynamically adjusts the early warning level to ensure the real-time performance and accuracy of the early warning.

[0147] The specific steps for S6 remote operation and maintenance linkage are as follows:

[0148] S6.1: The main control module integrates various data such as the operating status, faults, and early warnings of each terminal module, and uploads the data to the distribution network automation master station through RS485 bus and Ethernet. The master station analyzes the uploaded data and issues remote control commands according to the early warning level and fault conditions, which are then forwarded to the main control module through the fault early warning module.

[0149] S6.2: Based on the early warning information and fault location data from the main station, maintenance personnel formulate plans and conduct precise on-site repairs. After the repairs are completed, the main control module updates the fault records and operating parameters, the fault early warning module cancels the warning, and the terminal returns to normal. Simultaneously, the maintenance data is stored and used to update relevant parameters for fault probability calculation and optimize the fuzzy PID collaborative control algorithm, achieving a closed loop between maintenance and algorithm optimization, thus improving early warning accuracy and module collaboration efficiency.

[0150] The present invention provides an embodiment 3: The system of this embodiment is applicable to the 10kV outdoor pole-mounted distribution network automation terminal, and the whole includes a main control module, a telemetry module, a remote signaling module, a remote control module, an environmental monitoring module, a fault self-diagnosis module, an intelligent protection module, a power supply voltage stabilization and protection module, a fault early warning module and a storage module.

[0151] The main control module uses an industrial-grade chip and connects to the environmental monitoring module, fault self-diagnosis module, intelligent protection module, power supply voltage regulation and protection module, and storage module via an RS485 bus. The communication baud rate is set to 9600bps, with 8 data bits, 1 stop bit, and no parity bit. The fault early warning module is equipped with an Ethernet processing chip and communicates with the main control module and the distribution network automation master station using the TCP / IP protocol. Its static IP address is set to 192.168.1.100, the communication port is 8080, and CRC16 checksum is used to ensure data transmission stability.

[0152] The environmental monitoring module consists of an internal temperature and humidity sensor, an external temperature and humidity sensor, a dust concentration sensor, and voltage and current sensors. The internal temperature and humidity sensor is located on the upper part of the PCB board inside the terminal housing, the external temperature and humidity sensor is installed inside the rainproof cover on the outside of the terminal housing, the dust concentration sensor is located at the air inlet of the terminal, and the voltage and current sensors are connected to the power input terminal of the terminal. All sensors collect data at a frequency of 5 seconds. The raw data is first corrected for errors using preset coefficients, then processed by a moving average filtering algorithm before being transmitted to the main control module. The number of filtering windows is set to 10, and the sensor calibration coefficients are set to 0.02 and 0.1, respectively.

[0153] The fault self-diagnosis module incorporates two types of subroutines: hardware detection and software detection. The hardware detection subroutine monitors the on / off status and performance degradation of the power module, communication module, acquisition module, and execution module in real time. A hardware fault is identified when the hardware operating parameters deviate from the standard parameters by 5%. The software detection subroutine monitors the program's response time and data transmission packet loss rate. A software fault is identified when the program response time exceeds 200 milliseconds or the data packet loss rate exceeds 1%. For four minor faults—program freeze, communication link interruption, data transmission packet loss, and slight drift of the acquisition module—the module automatically performs software reset, communication re-handshake, data retransmission, and acquisition parameter calibration. The self-repair process retryes three times; if the retry fails, the fault information is uploaded to the main control module.

[0154] The intelligent protection module includes a three-stage speed-regulating heat dissipation unit and a dustproof sealing unit. The heat dissipation unit uses a 12V DC fan with aluminum heat sinks, implementing three-stage control based on the internal temperature of the terminal. When the temperature is below 25 degrees Celsius, the fan stops running; when the temperature is between 25 and 40 degrees Celsius, the fan runs at a low speed of 1200 rpm; and when the temperature is above 40 degrees Celsius, the fan runs at a high speed of 2400 rpm. The PID parameters for the low-speed operation are set to a proportional coefficient of 2.0 and an integral coefficient of 0.1, while the PID parameters for the high-speed operation are set to a proportional coefficient of 3.0 and an integral coefficient of 0.2. The dustproof sealing unit is equipped with an electrically operated sealing baffle, a 10-micron pore size dust filter, and a filter pressure differential sensor. The opening and closing degree of the baffle is adjusted according to the dust concentration using an exponential decay algorithm. When the pressure difference between the inside and outside of the filter reaches 1.5 kPa, the module issues a filter cleaning reminder signal.

[0155] The power supply voltage regulation and protection module consists of a surge protector, a linear voltage regulator module, and an undervoltage and overvoltage protection module connected in series. The surge protector is a 40kA surge protector. The linear voltage regulator module can stably output 12V DC from the input voltage, with the voltage deviation controlled within ±0.2V. The terminal's rated operating voltage is AC 220V, the voltage fluctuation coefficient is 0.1, the undervoltage protection threshold is set to 198V, and the overvoltage protection threshold is set to 242V. When the input voltage exceeds the threshold range, the module automatically cuts off the terminal power supply within 0.5 seconds and feeds back the protection signal to the main control module.

[0156] The fault early warning module classifies warning levels into three levels based on the probability of fault occurrence: a 30% to 50% probability is considered a minor warning, 50% to 80% a medium warning, and 80% or higher a severe warning. The warning thresholds are derived from six months of outdoor trial operation data from the terminal. Warning information is simultaneously displayed at the terminal site and at the main station. Different colored lights at the terminal site distinguish the warning status, while the main station simultaneously receives warning and fault location data. In the case of a severe warning, the terminal automatically suspends non-core operating functions to prevent the fault from escalating.

[0157] The storage module uses flash memory chips with a storage capacity of 16MB. It adopts a circular storage mechanism and can store up to 10,000 records of running data. Once the storage capacity reaches the limit, it automatically overwrites the oldest historical records. It is used to save historical fault data of the terminal, real-time running parameters, and various preset calibration parameters.

[0158] Methods to reduce the failure rate of distribution network automation terminals

[0159] When applied to the system described in Example 1, it is executed sequentially in six steps.

[0160] In the multi-parameter collaborative monitoring step, various sensors of the environmental monitoring module collect raw data on temperature and humidity, dust concentration, power supply voltage and current inside and outside the terminal at a frequency of once every 5 seconds. The data is first corrected for errors by a preset coefficient, and then noise is removed by a moving average filtering algorithm. The processed data is synchronously transmitted to the main control module and the fault early warning module. The main control module writes the data into the storage module in a circular storage mode, thus completing the data collection, processing, transmission and storage.

[0161] In the real-time fault self-diagnosis and self-repair process, the hardware and software detection subroutines of the fault self-diagnosis module synchronously detect the status of each component of the terminal every 5 seconds. The fault type is determined by parameter comparison and threshold judgment, and the fault code location technology is used to pinpoint the fault location. For minor faults caused solely by software issues, self-repair operations such as reset, calibration, and retransmission are automatically performed, with the repair process retried 3 times. For hardware faults or software faults that cannot be self-repaired, the fault information is stored in historical data, and a fault warning process is initiated.

[0162] In the feedback-based environmental protection and control process, the main control module sends control commands to the intelligent protection module based on the processed temperature and dust concentration data. The heat dissipation process controls the fan speed at three levels through a segmented PID algorithm, while adaptively correcting the PID parameters to ensure stable temperature control. The dust prevention process adjusts the opening and closing of the sealing baffle according to the dust concentration. When the filter pressure difference reaches the threshold, a cleaning reminder is issued. The overall protection follows the logic of prioritizing heat dissipation, ensuring unobstructed heat dissipation channels under high temperature conditions.

[0163] In the entire power supply protection process, the power supply voltage regulation and protection module acquires input voltage and current data in real time. When an input voltage surge occurs, the surge protector starts within 0.1 microseconds and absorbs the surge current to suppress voltage changes. The linear voltage regulator module continuously stabilizes the output voltage. The undervoltage and overvoltage protection module monitors the voltage status in real time. When the voltage exceeds the rated range, it quickly cuts off the power supply and feeds back the protection event to the main control module for storage and early warning.

[0164] In the fault classification and early warning process, the fault early warning module retrieves historical fault data and preset calibration parameters from the storage module over the past 6 months. Combining real-time environmental data and fault diagnosis data, it calculates the component failure probability using a Bayesian estimation algorithm. The probability calculation result is updated every 5 seconds. Based on the probability range, the corresponding level of early warning is triggered. Different levels of early warning execute differentiated information uploading and terminal control operations. In the event of a severe early warning, non-core functions are suspended to reduce the risk of failure.

[0165] In the remote operation and maintenance linkage process, the main control module integrates terminal operating status, fault information, and early warning data, and uploads them to the distribution network automation master station via RS485 bus and Ethernet. The master station issues remote control commands according to the early warning level: for a minor early warning, it remotely reads operating parameters; for a medium early warning, it remotely restarts the terminal; and for a severe early warning, it remotely cuts off non-core power supply. Maintenance personnel conduct precise on-site repairs based on the fault location data. After repairs are completed, the fault record is updated, the early warning status is lifted, and the maintenance data is synchronously stored in the storage module for optimizing algorithm parameters and control logic, forming a closed loop between maintenance and system optimization.

[0166] Field tests and effect verification

[0167] This embodiment selects an outdoor pole-mounted terminal of a 10kV distribution network in a prefecture-level city for field testing. The test period is 6 months, and the test environment includes typical operating conditions such as high summer temperature, high outdoor dust, and power supply voltage fluctuation. Two sets of comparison objects are set up in the test: one set is the terminal equipped with the system and method of this invention, and the other set is the traditional conventional terminal. The number of terminals in each set is 10.

[0168] During the trial, the terminal's operational status was continuously monitored. The annual failure rate of traditional conventional terminals was 8.2%, while the annual failure rate of terminals equipped with this invention dropped to 1.2%, a reduction of over 85%. Traditional terminals lacked self-repair capabilities for minor faults, while terminals equipped with this invention achieved a 92.3% self-repair rate for minor faults, a 96.7% accuracy rate for fault warnings, and a 100% success rate for power supply anomaly protection. Regarding maintenance costs, the annual maintenance cost per unit for traditional terminals was 1280 yuan, while the annual maintenance cost per unit for terminals equipped with this invention dropped to 210 yuan, a reduction of over 83%.

[0169] Test results show that this invention, through multi-module collaborative operation and full-process control, can effectively reduce the failure rate of distribution network automation terminals, improve the self-repair capability of minor faults, achieve early warning and accurate fault location, and significantly reduce operation and maintenance costs. The system adopts a modular design and can be directly installed inside existing terminals without modifying the original terminal structure and installation method. It is compatible with various outdoor distribution network automation terminals and has good application value.

[0170] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A system for reducing the failure rate of distribution network automation terminals, characterized in that, include: It includes a main control module, telemetry module, remote signaling module, remote control module, environmental monitoring module, fault self-diagnosis module, intelligent protection module, power supply voltage regulation and protection module, fault early warning module and storage module; The telemetry module, remote signaling module, remote control module, environmental monitoring module, fault self-diagnosis module, intelligent protection module, power supply voltage regulation and protection module, and storage module are all electrically connected to the main control module. The fault early warning module is electrically connected to the main control module and is also communicatively connected to the distribution network automation master station. The main control module is the core control module of the distribution network terminal. It receives the collected and detected data from each module and realizes the coordinated work of each module according to the preset control logic. The telemetry module, telesignal module, and remote control module are used to realize the core functions of telemetry, telesignal, and remote control of the distribution network automation terminal. The storage module is used to store the terminal's historical fault data, operating parameters, and preset calibration parameters. The environmental monitoring module collects environmental parameters inside and outside the terminal, as well as voltage and current parameters at the power input terminal, in real time, and transmits the collected data to the main control module. The collected data is also transmitted to the fault early warning module as real-time operation data. The fault self-diagnosis module performs real-time fault detection and location on the terminal's hardware units, software programs, and communication links, and feeds back the diagnostic results to the main control module. It can also perform self-repair operations on minor non-hardware damage faults that can be resolved by software reset or parameter reset, and its diagnostic data is synchronously transmitted to the fault early warning module as real-time running data. Real-time data from the environmental monitoring module and the fault self-diagnosis module are synchronized to the fault early warning module and the storage module via the main control module, serving as the basic data for fault trend analysis; The intelligent protection module receives control commands from the main control module, implements three-level speed regulation heat dissipation based on temperature parameters collected by the environmental monitoring module, and completes dustproof sealing regulation based on dust concentration parameters; the three-level feedback speed regulation heat dissipation includes three states: off, low-speed operation, and high-speed operation. The power supply voltage regulation and protection module is connected in series at the terminal power supply input terminal to realize power supply surge protection, input voltage regulation and undervoltage and overvoltage protection; The fault early warning module has a built-in fault trend analysis algorithm. It uses environmental and power supply parameters collected by the environmental monitoring module and diagnostic data from the fault self-diagnosis module as real-time operating data. Combined with historical fault data of the distribution network terminal provided by the storage module, it calculates the probability of fault occurrence of each component through data comparison and analysis, sets three-level early warning thresholds to realize fault graded early warning, and uploads the early warning information and fault location data to the distribution network automation master station.

2. The system for reducing the failure rate of distribution network automation terminals according to claim 1, characterized in that, The environmental monitoring module includes an internal temperature and humidity sensor inside the terminal housing, an external temperature and humidity sensor outside the terminal housing, a dust concentration sensor, and a voltage and current sensor at the power input terminal; each sensor collects parameters every 5 seconds, and all of them achieve real-time data interaction with the main control module.

3. The system for reducing the failure rate of distribution network automation terminals according to claim 1, characterized in that, The fault self-diagnosis module has built-in hardware detection subroutines and software detection subroutines; The hardware detection subroutine is used to detect the on / off status and performance degradation of the terminal power module, communication module, acquisition module, and execution module; the software detection subroutine is used to detect abnormal states in terminal program operation, data transmission, and instruction execution. Minor non-hardware damage faults that can be resolved by software reset or parameter reset include program freezes, communication link interruptions, data transmission packet loss, and slight drift of the acquisition module.

4. The system for reducing the failure rate of distribution network automation terminals according to claim 1, characterized in that, The intelligent protection module includes a three-level speed-regulating heat dissipation unit based on temperature feedback and a dustproof sealing unit based on dust concentration feedback. The three-stage speed-regulating heat dissipation unit is a combination structure of a temperature-controlled three-stage speed-regulating heat dissipation fan and a heat sink. The three-stage speed regulation is based on the temperature parameters collected by the environmental monitoring module received by the main control module to achieve feedback control. Specifically, the fan is turned off when the temperature is below 25℃, the fan runs at low speed when the temperature is greater than or equal to 25℃ and less than or equal to 40℃, and the fan runs at high speed when the temperature is above 40℃. The dustproof sealing unit includes an electric sealing baffle, a dustproof filter, and a filter differential pressure sensor, all of which are intelligently controlled by the main control module based on the parameters of the environmental monitoring module.

5. The system for reducing the failure rate of distribution network automation terminals according to claim 1, characterized in that, The power supply voltage stabilization and protection module is composed of a surge protector, a voltage stabilization module and an undervoltage and overvoltage protection module connected in series. The undervoltage and overvoltage protection module automatically cuts off the power supply to the distribution network terminal when the input voltage exceeds the terminal's rated operating range.

6. The system for reducing the failure rate of distribution network automation terminals according to claim 1, characterized in that, The three-level warning thresholds of the fault warning module are: light warning corresponds to a fault occurrence probability of 30%~50%, medium warning corresponds to a fault occurrence probability of 50%~80%, and heavy warning corresponds to a fault occurrence probability of ≥80%. The warning mode includes terminal field warning and distribution network automation master station remote warning. The threshold is a preset calibration parameter stored in the storage module. This parameter is derived from the 6-month trial operation data of the distribution network terminal. By comparing the failure rate of the distribution network terminal before and after the transformation, the failure probability range corresponding to each warning level is determined to ensure the accuracy and effectiveness of the warning.

7. The system for reducing the failure rate of distribution network automation terminals according to claim 1, wherein the main control module is connected to the environmental monitoring module, the fault self-diagnosis module, the intelligent protection module, the power supply voltage stabilization and protection module, and the storage module via an RS485 bus, and the fault early warning module is connected to the main control module and the distribution network automation master station via an Ethernet.

8. A method for reducing the failure rate of distribution network automation terminals, characterized in that, The system for reducing the failure rate of distribution network automation terminals as described in any one of claims 1-7 includes the following steps: S1: Multi-parameter collaborative monitoring: The environmental monitoring module collects temperature and humidity, dust concentration, power supply voltage and current parameters inside and outside the distribution network terminal at a preset frequency and transmits them to the main control module in real time. S2: Real-time self-diagnosis and self-repair of faults: The fault self-diagnosis module detects the status of terminal hardware, software and communication links in real time, locates the fault point, and automatically performs self-repair operation when it detects minor faults that are not hardware damage and can be resolved by software reset or parameter reset. When it detects medium or severe faults, it feeds back the fault information to the main control module, and the main control module stores the fault information in the storage module as historical fault data. S3: Feedback-based environmental protection control: Based on environmental monitoring data, the main control module controls the intelligent protection module to complete the three-level speed regulation of the cooling fan and the opening and closing degree of the dustproof sealing baffle. S4: Full Power Supply Protection: The power supply voltage regulation module absorbs and regulates the input voltage surge. In case of abnormal voltage, it triggers undervoltage or overvoltage protection to cut off the power supply. S5: Fault Classification Early Warning: The fault early warning module calls historical fault data and preset calibration parameters from the storage module, combines them with real-time data transmitted from the environmental monitoring module and the fault self-diagnosis module to perform trend analysis, calculate the fault probability and trigger the corresponding level of early warning, and uploads the early warning and fault location data to the distribution network automation master station; S6: Remote Operation and Maintenance Linkage: The distribution network terminal uploads its operating status, fault diagnosis, and early warning information to the master station in real time. The master station issues remote control commands to realize remote management and control of the terminal. Operation and maintenance personnel perform early intervention and precise maintenance based on early warning and location data.

9. The method according to claim 8, characterized in that, The specific steps of the S1 multi-parameter collaborative monitoring are as follows: S1.1: After the environmental monitoring module is started, various sensors collect raw data such as temperature and humidity inside and outside the terminal, dust concentration, and power supply voltage and current at a frequency of 5 seconds. The collected raw data is first corrected for error by a preset coefficient, and then noise is reduced by a moving average filtering algorithm to obtain accurate real-time monitoring data. S1.2: The processed data is synchronously transmitted to the main control module and the fault early warning module (as the basis for fault analysis). At the same time, the main control module stores the filtered data to the storage module through a cyclic storage algorithm, realizing the accurate acquisition, processing, transmission and storage of multiple parameters. The specific steps for real-time self-diagnosis and self-repair of the S2 fault are as follows: S2.1: The fault self-diagnosis module starts hardware and software detection subroutines, and synchronously detects the status of each component of the terminal every 5 seconds with the main control module. Hardware detection compares the collected operating parameters with preset standard parameters and uses a threshold judgment algorithm to determine hardware faults. Software detection compares the collected program response time and data transmission packet loss rate with preset thresholds to determine software faults. S2.2: When a hardware or software fault is detected, the faulty component and type are determined by fault code location technology and fed back to the main control module. For minor faults that are only software faults and have a low degree of impact, the software reset or parameter reset is automatically performed for self-repair. After repair, the fault record is updated. For hardware faults or software faults that cannot be self-repaired, the fault information is fed back to the main control module, which stores it as historical fault data and triggers the fault warning module to prepare. The specific steps of the S3 feedback-based environmental protection control are as follows: S3.1: The main control module receives the filtered internal temperature and dust concentration data transmitted by the environmental monitoring module, and issues control commands to the intelligent protection module according to the preset control logic. In terms of heat dissipation, a segmented PID algorithm is used to realize three-level speed regulation of the cooling fan. The fan is controlled to shut down, run at low speed or high speed according to different temperature ranges. At the same time, the PID parameters are dynamically adjusted through an adaptive correction algorithm to ensure stable temperature control. S3.2: In terms of dust prevention, an exponential decay algorithm is adopted to intelligently adjust the opening and closing degree of the electric sealing baffle according to the dust concentration. In addition, the filter differential pressure sensor monitors the pressure inside and outside the filter in real time. When the pressure difference reaches the preset threshold, the main control module sends a filter cleaning reminder signal and transmits it to the fault early warning module as auxiliary early warning information.

10. The method according to claim 8, characterized in that, The specific steps for the full-process protection of S4 power supply are as follows: S4.1: The power supply voltage regulation and protection module is connected in series at the power supply input terminal of the terminal and receives input voltage and current data transmitted by the environmental monitoring module in real time; when a surge occurs in the input voltage, the surge protector automatically starts to absorb the surge current and suppress voltage surges to protect the internal circuit of the terminal. S4.2: The input voltage is regulated by a linear voltage regulation algorithm to ensure that the output voltage meets the rated operating requirements of the terminal. The input voltage is monitored in real time by a threshold judgment algorithm. Based on the preset undervoltage and overvoltage thresholds, when the input voltage exceeds the rated range, the terminal power supply is automatically cut off and a protection signal is fed back to the main control module. The main control module stores the event and triggers a fault warning. The specific steps for the S5 fault classification and early warning system are as follows: S5.1: The fault early warning module first calls the historical fault data in the storage module, the trial operation and actual operation records of the past 6 months and the preset calibration parameters, and combines the real-time data of the environmental monitoring module and the diagnostic data of the fault self-diagnosis module to calculate the probability of each component failure using the Bayesian estimation algorithm. S5.2: Based on the probability range of fault occurrence, the system determines the three levels of early warning (light, medium, and heavy) and no early warning status through the early warning trigger function; different levels of early warning correspond to different on-site prompts and data upload operations. During heavy early warning, non-core terminal functions will be suspended to prevent the fault from escalating; the fault early warning module updates the fault probability calculation results every 5 seconds and dynamically adjusts the early warning level to ensure the real-time performance and accuracy of the early warning. The specific steps for the S6 remote operation and maintenance linkage are as follows: S6.1: The main control module integrates various data such as the operating status, faults, and early warnings of each terminal module, and uploads the data to the distribution network automation master station through RS485 bus and Ethernet. The master station analyzes the uploaded data and issues remote control commands according to the early warning level and fault conditions, which are then forwarded to the main control module through the fault early warning module. S6.2: Based on the early warning information and fault location data from the main station, maintenance personnel formulate plans and perform precise on-site repairs. After the repairs are completed, the main control module updates the fault records and operating parameters, the fault early warning module cancels the warning, and the terminal returns to normal. At the same time, the maintenance data is stored and used to update relevant parameters for fault probability calculation and optimize the fuzzy PID collaborative control algorithm, thereby realizing a closed loop between maintenance and algorithm optimization and improving the accuracy of early warnings and the efficiency of module collaboration.

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