Power distribution terminal intelligent management system and method
By setting up monitoring areas and sensors within power distribution terminal equipment and establishing a monitoring threshold analysis model, combined with historical data and probability analysis, the problem of inaccurate fault judgment in existing technologies has been solved, achieving highly accurate fault early warning and reducing the risk of equipment damage.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-08
- Publication Date
- 2026-03-13
AI Technical Summary
In existing technologies, fault diagnosis of power distribution terminals relies on threshold comparison methods, which cannot accurately reflect the actual operating status of the equipment. This leads to the failure to handle initial faults in a timely manner, which may result in equipment damage or downtime. Furthermore, there are issues of false alarms and frequent interventions.
By setting up multiple monitoring zones within the power distribution terminal equipment, installing environmental sensors and current and voltage sensors, establishing a monitoring threshold analysis model, training the first and second monitoring thresholds based on historical data, and combining probability analysis to determine the equipment status, intelligent early warning can be achieved.
It improves the accuracy of power distribution terminal fault prediction, reduces the risk of equipment safety accidents, and can promptly detect hidden faults and provide early warnings.
Smart Images
Figure CN121663802A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of intelligent early warning technology for power distribution networks, specifically to an intelligent management system and method for power distribution terminals. Background Technology
[0002] As a crucial link connecting the generation side and the user side, the stability of the distribution terminal directly affects the reliable power supply of the power system. With the continuous growth of electricity demand, fault early warning of the distribution network has become particularly important. Traditional fault detection methods that rely on manual monitoring suffer from low efficiency and poor accuracy. Therefore, modern distribution terminal early warning systems adopt artificial intelligence technology to identify fault modes and abnormal behaviors of distribution terminals by processing and analyzing a large amount of historical data, thereby reducing the risk of equipment failure.
[0003] Existing methods for fault diagnosis of power distribution terminals often rely on setting thresholds for comparison. However, this method cannot accurately reflect the actual operating status of the equipment. If the threshold is set too high, some important abnormal signals may be ignored, while if the threshold is set too low, it may be affected by electromagnetic interference, leading to false alarms and frequent interventions. In the early stages of equipment failure, the severity of the failure may not immediately cause the monitoring factors to exceed the set threshold. Furthermore, the system's insufficient analysis capabilities may result in these early failures not being handled in a timely manner, ultimately leading to serious equipment damage or shutdown. Summary of the Invention
[0004] The purpose of this invention is to provide a technical solution to solve the problems raised in the prior art.
[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for intelligent management of power distribution terminals, the method comprising the following steps: S1. Several monitoring zones are set up for the power distribution terminal equipment, and environmental data and current and voltage data generated in each monitoring zone during the operation of the power distribution terminal equipment are collected; wherein, each monitoring zone contains several environmental data collection points; the environmental data includes changes in environmental factors in different monitoring zones; S2. Based on historical environmental data and historical current and voltage data, train the monitoring threshold analysis model, determine the first and second monitoring thresholds for fault early warning of power distribution terminal equipment, and obtain the error value of the monitoring threshold analysis model for environmental factor prediction based on the second monitoring threshold and environmental factors in historical environmental data. S3. Based on the collected environmental data, determine the environmental factors of each environmental data collection point within the current power distribution terminal equipment, and predict the status of each monitoring area within the power distribution terminal equipment based on the first monitoring threshold determined in the monitoring threshold analysis model and the magnitude of the predicted error value; based on the predicted status of each monitoring area within the power distribution terminal equipment, determine whether the current power distribution terminal equipment has malfunctioned through probability analysis. S4. Issue early warnings for faulty power distribution terminal equipment and send fault information to management personnel.
[0006] Furthermore, the power distribution terminal equipment is equipped with a number of environmental sensors and current and voltage sensors; the installation positions of the environmental sensors are evenly distributed in each monitoring area inside the power distribution terminal equipment; the number of monitoring areas is not less than 1, and the number of environmental sensors installed in each monitoring area is not less than 1.
[0007] Furthermore, the method steps of step S2 are as follows: S21. Establish a monitoring threshold analysis model, filter historical data on power distribution terminal equipment failures from the database, determine the changes in environmental factors collected by different environmental sensors in the historical data when the power distribution terminal equipment failure occurred, and obtain a matrix. ; S22, according to Determine the first monitoring threshold for different environmental sensors. To satisfy the following conditions: ; in, This represents the first monitoring threshold of the i-th environmental sensor; This represents the maximum value of the environmental factor collected by the i-th environmental sensor at the corresponding location over time t in different historical data of the occurrence of power distribution terminal equipment failure; ; S23. Filter historical data of normal operation of power distribution terminal equipment from the database, analyze the relationship between changes in environmental factors collected by different environmental sensors and changes in current and voltage in the monitoring area at the corresponding installation location when the power distribution terminal equipment is safe, and determine the second monitoring threshold of different environmental sensors. .
[0008] Furthermore, the method steps of step S3 are as follows: S31. Analyze the collected environmental data to obtain the environmental factors collected by different environmental sensors at corresponding locations at the current time. It obtains the environmental factors collected by different environmental sensors at their corresponding locations at the previous moment, as well as the current and voltage values of the monitoring area at the corresponding sensor installation location at the previous moment. Based on the relationship between changes in environmental factors and changes in the current and voltage of the monitoring area at the corresponding installation location, it predicts the second monitoring threshold of different environmental sensors at the current moment. ; S32. Determine the number of environmental sensors installed in each monitoring area. ,Will , and Compare them separately to determine the magnitude of the prediction error for environmental factors. : And predict the status of each monitoring area within the power distribution terminal equipment; among which, This represents the environmental factors collected by the i-th environmental sensor at the corresponding location at the current moment; This represents the second monitoring threshold of the i-th environmental sensor at the current time.
[0009] Furthermore, the method for determining whether the current power distribution terminal equipment has malfunctioned is as follows: S10, when and All meet At that time, determine the conditions in each monitoring area separately. Number of environmental sensors ; Determine the conditions in each monitoring area respectively Number of environmental sensors ;according to and Determine the probability that each monitored area is in a normal state. Determine the probability of risk in the status of each monitoring area. : ; ; according to and Determine the probability P of a power distribution terminal equipment failure: ; Determine the fault threshold K of the power distribution terminal equipment; compare K with P; when When, determine the safety of the power distribution terminal equipment; when When this happens, it is determined that a fault has occurred in the power distribution terminal equipment; in, This represents the environmental factors collected by the i-th environmental sensor at the corresponding location at the current moment; This represents the second monitoring threshold of the i-th environmental sensor at the current time; ; ; ; ; ; ; This represents the number of environmental sensors installed in the j-th monitoring zone; This indicates that the j-th monitoring area meets the condition. , The number of environmental sensors; This indicates that the j-th monitoring area meets the condition. , The number of environmental sensors; The probability that the j-th monitoring area is in a normal state; The probability that the j-th monitoring area is at risk; S20, when exists When the monitoring area corresponding to the installation location of the i-th environmental sensor is determined to be faulty, the power distribution terminal equipment is directly determined to be faulty.
[0010] The intelligent management system for power distribution terminals includes a data acquisition and transmission module, a database, a model management module, an intelligent computing module, and an intelligent early warning module. The data acquisition and transmission module is used to acquire environmental data and current and voltage data generated during the operation of the power distribution terminal equipment; the power distribution terminal equipment contains several monitoring areas; The database is used to store the collected environmental data and current and voltage data as historical data. The model management module is used to establish a monitoring threshold analysis model based on historical environmental data and historical current and voltage data in the database, and to determine the first and second monitoring thresholds for fault early warning of power distribution terminal equipment. The intelligent computing module is used to determine the environmental factors of the current power distribution terminal equipment based on the collected environmental data; predict the status of each monitoring area within the power distribution terminal equipment based on the environmental factors of the current power distribution terminal equipment, the first monitoring threshold and the second monitoring threshold for fault warning of the power distribution terminal equipment; and determine whether the current power distribution terminal equipment has malfunctioned based on the prediction results of the status of each monitoring area within the power distribution terminal equipment. The intelligent early warning module is used to issue early warnings for faulty power distribution terminal equipment and send fault information to management personnel.
[0011] Furthermore, a mobile user terminal is provided to digitally display the environmental factors within the current power distribution terminal equipment, the probability of risks in the status of each monitoring area, and the probability of power distribution terminal equipment failure. Managers can view these information through the mobile user terminal.
[0012] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: by calculating the first and second monitoring thresholds of the power distribution terminal equipment through historical data, the collected environmental data is analyzed more comprehensively, thereby improving the accuracy of fault prediction of the power distribution terminal equipment; by fusing multiple sets of data, the status of the power distribution terminal equipment is comprehensively judged, solving the problem that the failure to detect the fault is caused by the insignificant changes in environmental factors in the early stage of equipment failure; and by intelligent early warning, the risk of safety accidents of the power distribution terminal equipment is reduced. Attached Figure Description
[0013] Figure 1This is a schematic diagram of the steps of the intelligent management method for power distribution terminals of the present invention. Detailed Implementation
[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0015] Please see Figure 1 The present invention provides the following technical solution: Please see Figure 1 In this first embodiment, a method for intelligent management of power distribution terminals is provided, which includes the following steps: S1. Several monitoring zones are set up for the power distribution terminal equipment, and environmental data and current and voltage data generated in each monitoring zone are collected during the operation of the power distribution terminal equipment; wherein, each monitoring zone contains several environmental data collection points; the environmental data includes the changes of environmental factors in different monitoring zones.
[0016] Furthermore, the power distribution terminal equipment is equipped with several environmental sensors and current and voltage sensors; the environmental sensors are evenly distributed in each monitoring area inside the power distribution terminal equipment; the number of monitoring areas is not less than one, and the number of environmental sensors installed in each monitoring area is not less than one; by evenly installing multiple environmental sensors inside the power distribution terminal equipment, abnormal status information of the power distribution terminal equipment can be reflected more accurately, thereby improving the accuracy and reliability of data analysis. The more monitoring areas on the power distribution terminal equipment, the higher the accuracy of fault warning.
[0017] In this embodiment, fault warning is provided for the power distribution terminal equipment. The environmental data includes, but is not limited to, temperature, equipment amplitude, and electromagnetic intensity. Current and voltage sensors are installed at the input and output terminals of the monitoring area inside the power distribution terminal equipment, as well as at key nodes of the internal circuit. The current and voltage at the corresponding environmental sensor are determined based on the installation location of the environmental sensor.
[0018] S2. Based on historical environmental data and historical current and voltage data, train the monitoring threshold analysis model, determine the first and second monitoring thresholds for fault early warning of power distribution terminal equipment, and obtain the error value of the monitoring threshold analysis model for predicting environmental factors according to the second monitoring threshold and environmental factors in historical environmental data.
[0019] Specifically, the steps are as follows: S21. Establish a monitoring threshold analysis model, filter historical data on power distribution terminal equipment failures from the database, determine the changes in environmental factors collected by different environmental sensors in the historical data when the power distribution terminal equipment failure occurred, and obtain a matrix. ; in, ; The expression represents the curves of environmental factors collected by different environmental sensors at corresponding locations over time t in the m historical data of power distribution terminal equipment failures analyzed; m represents the number of historical data entries of power distribution terminal equipment failures selected; n represents the number of environmental sensors installed in the power distribution terminal equipment; and t represents the timestamp. S22, according to Determine the first monitoring threshold for different environmental sensors. To satisfy the following conditions: ; in, This represents the first monitoring threshold of the i-th environmental sensor; This represents the maximum value of the environmental factor collected by the i-th environmental sensor at the corresponding location over time t in different historical data of the occurrence of power distribution terminal equipment failure; ; S23. Filter historical data of normal operation of power distribution terminal equipment from the database, analyze the relationship between changes in environmental factors collected by different environmental sensors and changes in current and voltage in the monitoring area at the corresponding installation location when the power distribution terminal equipment is safe, and determine the second monitoring threshold of different environmental sensors. .
[0020] In this implementation, taking temperature as an example of environmental factors, the second monitoring threshold for different environmental sensors is determined according to the calculation formula: ; Among them, according to and To determine the magnitude of the error value of the monitoring threshold analysis model for predicting environmental factors. ; in, This represents the second monitoring threshold of the i-th environmental sensor at time t; This represents the environmental factor collected by the i-th environmental sensor at time t-1; This represents the environmental factor collected by the i-th environmental sensor at time t; This represents the voltage in the monitoring area at the location of the i-th environmental sensor at time t-1. This represents the current in the monitoring area at the installation location of the i-th environmental sensor at time t-1. This represents the heat conversion efficiency of the monitoring area at the installation location of the i-th environmental sensor at time t-1. This represents the temperature difference between the monitored area and the surrounding air at the location of the i-th environmental sensor at time t-1. This represents the convective heat transfer coefficient between the monitoring area and the surrounding air at the installation location of the i-th environmental sensor. This represents the surface area of the monitoring area at the installation location of the i-th environmental sensor; This represents the quality of the monitored area at the installation location of the i-th environmental sensor; This represents the specific heat capacity of the monitoring area at the installation location of the i-th environmental sensor; This represents the time step from t-1 to t.
[0021] In this embodiment, and It is determined directly through environmental data collected by the corresponding environmental sensors; and The determination is made directly using the current and voltage data collected by the corresponding current and voltage sensors. Taking temperature as an example, environmental factors are considered because some electrical energy is converted into heat energy during operation in the monitoring area of the power distribution terminal equipment. Furthermore, the heat conversion efficiency varies depending on the installation location of the environmental sensors. Therefore, the heat conversion efficiency at different installation locations of the environmental sensors is determined separately. Should be subject to and The effect of size; Determining this requires collecting the ambient air temperature from environmental sensors, based on the calculation formula: ;in, This represents the ambient air temperature around the sensor at time t-1. Due to factors such as sensor sensitivity and external interference, the calculated second monitoring threshold will have errors. Therefore, by... and By comparing the data, the magnitude of the error in temperature prediction by the monitoring threshold analysis model can be determined. Wherein, the magnitude of the error value pass To confirm, to confirm Meet the conditions , The smaller the value, the higher the accuracy of the monitoring threshold analysis model; the time step from t-1 to t is the response time step of the environmental sensor and the current and voltage sensor; in this embodiment, the response time steps of the environmental sensor and the current and voltage sensor are the same.
[0022] It should be noted that the power distribution terminal equipment failure indicates an increase in current and voltage caused by damage to internal components of the power distribution terminal equipment; since the increase in current and voltage when the power distribution terminal equipment fails will affect the surrounding environmental factors, the first monitoring threshold and the second monitoring threshold are determined by analyzing historical environmental data; the power distribution terminal equipment safety indicates that no power distribution terminal equipment failure has occurred.
[0023] It should be noted that the first monitoring threshold is used to determine the inevitable event of a power distribution terminal equipment failure; the first monitoring threshold and the second monitoring threshold are used to determine the accidental event of a power distribution terminal equipment failure; by calculating the first monitoring threshold and the second monitoring threshold, the problem that the failure cannot be detected due to the insignificant changes in environmental factors in the early stage of equipment failure is solved, thereby improving the accuracy of equipment failure analysis.
[0024] S3. Based on the collected environmental data, determine the environmental factors of each environmental data collection point within the current power distribution terminal equipment, and predict the status of each monitoring area within the power distribution terminal equipment based on the first monitoring threshold determined in the monitoring threshold analysis model and the magnitude of the predicted error value; based on the predicted status of each monitoring area within the power distribution terminal equipment, determine whether the current power distribution terminal equipment has malfunctioned through probability analysis. Specifically, the steps are as follows: The collected environmental data is analyzed to obtain the environmental factors collected by different environmental sensors at corresponding locations at the current time. It obtains the environmental factors collected by different environmental sensors at their corresponding locations at the previous moment, as well as the current and voltage values of the monitoring area at the corresponding sensor installation location at the previous moment. Based on the relationship between changes in environmental factors and changes in the current and voltage of the monitoring area at the corresponding installation location, it predicts the second monitoring threshold of different environmental sensors at the current moment. ; Determine the number of environmental sensors installed in each monitoring area. ,Will , and Compare them separately to determine the magnitude of the prediction error for environmental factors. : And predict the status of each monitoring area within the power distribution terminal equipment; among which, This represents the environmental factors collected by the i-th environmental sensor at the corresponding location at the current moment; This represents the second monitoring threshold of the i-th environmental sensor at the current time. S10, when and All meet At that time, determine the conditions in each monitoring area separately. Number of environmental sensors ; Determine the conditions in each monitoring area respectively Number of environmental sensors ;according to and Determine the probability that each monitored area is in a normal state. Determine the probability of risk in the status of each monitoring area. : ; ; according to and Determine the probability P of a power distribution terminal equipment failure: ; Determine the fault threshold K of the power distribution terminal equipment; compare K with P; when When, determine the safety of the power distribution terminal equipment; when When this happens, it is determined that a fault has occurred in the power distribution terminal equipment; in, This represents the environmental factors collected by the i-th environmental sensor at the corresponding location at the current moment; This represents the second monitoring threshold of the i-th environmental sensor at the current time; ; ; ; ; ; ; This represents the number of environmental sensors installed in the j-th monitoring zone; This indicates that the j-th monitoring area meets the condition. , The number of environmental sensors; This indicates that the j-th monitoring area meets the condition. , The number of environmental sensors; The probability that the j-th monitoring area is in a normal state; The probability that the j-th monitoring area is at risk; S20, when exists When the monitoring area corresponding to the installation location of the i-th environmental sensor is determined to be faulty, the power distribution terminal equipment is directly determined to be faulty.
[0025] Understandably, this is achieved by determining the probability of events in each monitored area being in a normal state and those at risk, and by... Normalization is performed to calculate the probability of power distribution terminal equipment failure. Because the analyzed environmental data is more comprehensive, it can better highlight the accuracy of system fault diagnosis.
[0026] It should be noted that the above judgment method is to prevent the system from ignoring some important abnormal signals of environmental factors. , That is, they exist simultaneously and In this case; at the same time, in this embodiment, if If the probability of a risk in the monitored area is 100%, then it is directly determined that the power distribution terminal equipment has malfunctioned; if That is, the probability that the monitored area is in a normal state is 100%, and the probability value corresponding to that monitored area is... and Not participating in probability The calculation is performed, and since the amount of environmental data involved in the calculation changes, the value of K needs to be redefined. The fault threshold K of the power distribution terminal equipment is determined based on the amount of environmental data involved in the calculation, that is, the number of monitoring areas involved in the calculation. The more environmental data involved in the calculation, the more accurate the determined threshold K becomes.
[0027] Understandable, through and The environmental data collected by each environmental sensor is analyzed separately. Since the monitoring thresholds are determined based on the historical data stored in the equipment itself, the analysis results of the environmental data collected by each environmental sensor are more accurate, thus revealing more hidden equipment faults.
[0028] S4. Issue early warnings for faulty power distribution terminal equipment and send fault information to management personnel.
[0029] In this second implementation: a power distribution terminal intelligent management system is provided, which includes a data acquisition and transmission module, a database, a model management module, an intelligent computing module, and an intelligent early warning module; The data acquisition and transmission module is used to acquire environmental data and current and voltage data generated during the operation of the power distribution terminal equipment; the power distribution terminal equipment contains several monitoring areas; The database is used to store the collected environmental data and current and voltage data as historical data. The model management module is used to establish a monitoring threshold analysis model based on historical environmental data and historical current and voltage data in the database, and to determine the first and second monitoring thresholds for fault early warning of power distribution terminal equipment. The intelligent computing module is used to determine the environmental factors of the current power distribution terminal equipment based on the collected environmental data; predict the status of each monitoring area within the power distribution terminal equipment based on the environmental factors of the current power distribution terminal equipment, the first monitoring threshold and the second monitoring threshold for fault warning of the power distribution terminal equipment; and determine whether the current power distribution terminal equipment has malfunctioned based on the prediction results of the status of each monitoring area within the power distribution terminal equipment. The intelligent early warning module is used to issue early warnings for faulty power distribution terminal equipment and send fault information to management personnel.
[0030] Furthermore, a mobile user terminal is provided to digitally display the environmental factors within the current power distribution terminal equipment, the probability of risks in the status of each monitoring area, and the probability of power distribution terminal equipment failure. Managers can view these information through the mobile user terminal.
[0031] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.
Claims
1. A method for intelligent management of power distribution terminals, characterized in that: The method includes the following steps: S1. Several monitoring zones are set up for the power distribution terminal equipment, and environmental data and current and voltage data generated in each monitoring zone during the operation of the power distribution terminal equipment are collected; wherein, each monitoring zone contains several environmental data collection points; the environmental data includes changes in environmental factors in different monitoring zones; S2. Based on historical environmental data and historical current and voltage data, train the monitoring threshold analysis model, determine the first and second monitoring thresholds for fault early warning of power distribution terminal equipment, and obtain the error value of the monitoring threshold analysis model for environmental factor prediction based on the second monitoring threshold and environmental factors in historical environmental data. S3. Based on the collected environmental data, determine the environmental factors of each environmental data collection point within the current power distribution terminal equipment, and predict the status of each monitoring area within the power distribution terminal equipment based on the first monitoring threshold determined in the monitoring threshold analysis model and the magnitude of the predicted error value; based on the predicted status of each monitoring area within the power distribution terminal equipment, determine whether the current power distribution terminal equipment has malfunctioned through probability analysis. S4. Issue early warnings for faulty power distribution terminal equipment and send fault information to management personnel.
2. The intelligent management method for power distribution terminals according to claim 1, characterized in that: The method steps of step S2 are as follows: S21. Establish a monitoring threshold analysis model, filter historical data on power distribution terminal equipment failures from the database, determine the changes in environmental factors collected by different environmental sensors in the historical data when the power distribution terminal equipment failure occurred, and obtain a matrix. ; S22, according to Determine the first monitoring threshold for different environmental sensors. To satisfy the following conditions: ； in, This represents the first monitoring threshold of the i-th environmental sensor; This represents the maximum value of the environmental factor collected by the i-th environmental sensor at the corresponding location over time t in different historical data of the occurrence of power distribution terminal equipment failure; ; S23. Filter historical data of normal operation of power distribution terminal equipment from the database, analyze the relationship between changes in environmental factors collected by different environmental sensors and changes in current and voltage in the monitoring area at the corresponding installation location when the power distribution terminal equipment is safe, and determine the second monitoring threshold of different environmental sensors. .
3. The intelligent management method for power distribution terminals according to claim 2, characterized in that: The method and steps for predicting the status of each monitoring area within the power distribution terminal equipment are as follows: S31. Analyze the collected environmental data to obtain the environmental factors collected by different environmental sensors at corresponding locations at the current time. It obtains the environmental factors collected by different environmental sensors at their corresponding locations at the previous moment, as well as the current and voltage values of the monitoring area at the corresponding sensor installation location at the previous moment. Based on the relationship between changes in environmental factors and changes in the current and voltage of the monitoring area at the corresponding installation location, it predicts the second monitoring threshold of different environmental sensors at the current moment. ; S32. Determine the number of environmental sensors installed in each monitoring area. ,Will , and Compare them separately to determine the magnitude of the prediction error for environmental factors. : And predict the status of each monitoring area within the power distribution terminal equipment; among which, This represents the environmental factors collected by the i-th environmental sensor at the corresponding location at the current moment; This represents the second monitoring threshold of the i-th environmental sensor at the current time.
4. The intelligent management method for power distribution terminals according to claim 3, characterized in that: The method for determining whether the current power distribution terminal equipment has malfunctioned is as follows: S10, when and All meet At that time, determine the conditions in each monitoring area separately. Number of environmental sensors ; Determine the conditions in each monitoring area separately. Number of environmental sensors ;according to and Determine the probability that each monitored area is in a normal state. Determine the probability of risk in the status of each monitoring area. : ； ； according to and Determine the probability P of a power distribution terminal equipment failure: ； Determine the fault threshold K of the power distribution terminal equipment; compare K with P; when When, determine the safety of the power distribution terminal equipment; when When this happens, it is determined that the power distribution terminal equipment has malfunctioned; in, This represents the environmental factors collected by the i-th environmental sensor at the corresponding location at the current moment; This represents the second monitoring threshold of the i-th environmental sensor at the current time; ; ; ; ; ; ; This represents the number of environmental sensors installed in the j-th monitoring zone; This indicates that the j-th monitoring area meets the condition. , The number of environmental sensors; This indicates that the j-th monitoring area meets the condition. , The number of environmental sensors; The probability that the j-th monitoring area is in a normal state; The probability that the j-th monitoring area is at risk; S20, when it exists When the monitoring area corresponding to the installation location of the i-th environmental sensor is determined to be faulty, the power distribution terminal equipment is directly determined to be faulty.
5. The intelligent management method for power distribution terminals according to claim 1, characterized in that: The power distribution terminal equipment is equipped with a number of environmental sensors and current and voltage sensors; the environmental sensors are evenly distributed in each monitoring area inside the power distribution terminal equipment; the number of monitoring areas is not less than 1, and the number of environmental sensors installed in each monitoring area is not less than 1.
6. A power distribution terminal intelligent management system, characterized in that: The system includes a data acquisition and transmission module, a database, a model management module, an intelligent computing module, and an intelligent early warning module; The data acquisition and transmission module is used to acquire environmental data and current and voltage data generated during the operation of the power distribution terminal equipment; the power distribution terminal equipment contains several monitoring areas; The database is used to store the collected environmental data and current and voltage data as historical data. The model management module is used to establish a monitoring threshold analysis model based on historical environmental data and historical current and voltage data in the database, and to determine the first and second monitoring thresholds for fault early warning of power distribution terminal equipment. The intelligent computing module is used to determine the environmental factors of the current power distribution terminal equipment based on the collected environmental data; predict the status of each monitoring area within the power distribution terminal equipment based on the environmental factors of the current power distribution terminal equipment, the first monitoring threshold and the second monitoring threshold for fault warning of the power distribution terminal equipment; and determine whether the current power distribution terminal equipment has malfunctioned based on the prediction results of the status of each monitoring area within the power distribution terminal equipment. The intelligent early warning module is used to issue early warnings for faulty power distribution terminal equipment and send fault information to management personnel.
7. The intelligent management system for power distribution terminals according to claim 6, characterized in that: It provides a mobile user terminal that digitally displays the environmental factors within the current power distribution terminal equipment, the probability of risks in each monitoring area, and the probability of power distribution terminal equipment failure. Managers can view this information through the mobile user terminal.