A wireless communication network management system and management method for automatic optimization

Abstract

The present invention discloses an automatically optimized wireless communication network management system and method, belonging to the technical field of electric power communication management, comprising an information acquisition module, used for acquiring text data generated by historical faults of a preset power grid, dividing the text data generated by the historical faults, and also used for acquiring the preset power grid operation state corresponding to the fault text data, a monitoring terminal, used for recording the communication base station and the communication base station operator matched with the preset power grid, and receiving the field data uploaded by the collection monitoring point, and updating the background data at the same time; the present invention utilizes the fault text data features, deeply learns and analyzes the power grid fault state corresponding to the data features, can judge the fault state occurring during the operation of the power grid according to the acquired real-time text data, and is more conducive to timely emergency repair deployment and daily operation and maintenance management of the power grid according to the mastered fault text data.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power communication management, and in particular to an automatically optimized wireless communication network management system and a management method. Background Art

[0002] Electricity is one of the most important energy sources in social, cultural life and industrial production. With the rapid development of my country's economy and the continuous improvement of people's living standards, electricity, as an important energy source in the future society, will inevitably develop towards marketization and informatization. According to the overall regulation of "separation of power plants and grids" of the national power department, the power department will become an enterprise mainly responsible for managing power grids. At this stage, the power department can transmit the collected power system data to the monitoring centers at the prefecture, city and provincial levels in real time to realize the unified monitoring and distributed management of power grid equipment. Among them, the unified monitoring and distributed management of the power grid mainly involves the real-time transmission of system data to the monitoring center when a fault occurs in the power grid, so that the monitoring center can The control center knows the fault status of the power grid under its jurisdiction. Most existing technologies provide wide-area wireless IP connections through China Mobile's GPRS system. In this process, system text data is automatically generated and transmitted to the monitoring center. However, the generated system text data is mostly generated and transmitted based on the final fault status, while the text data of the process of causing the fault is difficult to generate and communicate in real time. In this case, the monitoring center will not be able to receive various fault signals that appear during the operation of the power grid in a timely manner, thereby delaying the judgment of the operating status of the power grid. In extreme cases, it will hinder the emergency repair of the power grid and affect the daily operation and maintenance of the power grid. Summary of the invention

[0003] In view of the above problems existing in the existing power communication management, the present invention is proposed.

[0004] Therefore, one of the objects of the present invention is to provide an automatically optimized wireless communication network management system and method, which utilizes fault text data features, conducts deep learning analysis on the power grid fault status corresponding to the data features, and predicts and analyzes the fault situation of the power grid by analyzing the changing patterns of the text data and transmits it in real time. Then, the fault status occurring during the operation of the power grid is judged based on the acquired real-time text data, which is more conducive to timely emergency repair deployment and daily operation and maintenance management of the power grid based on the fault text data obtained.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] In one aspect, the present invention provides an automatically optimized wireless communication network management system, comprising:

[0007] An information acquisition module, used to acquire text data generated by historical faults of a preset power grid, divide the text data generated by the historical faults, and acquire a preset power grid operation state corresponding to the fault text data;

[0008] The monitoring terminal is used to record the communication base stations and communication base station operators that match the preset power grid, receive the field data uploaded by the collection monitoring point, and update the background data at the same time; when the fault text data of the preset power grid is obtained, a request for obtaining information on the fault status of the power grid line is initiated to the communication base station and the communication base station operator corresponding to the preset power grid;

[0009] A data fusion analysis unit, which responds to the historical fault text data acquired by the information acquisition module and is used to extract and analyze feature data in the historical fault text data. The data fusion analysis unit includes an analysis module, a communication module, and a management module;

[0010] The analysis module is used to analyze the number of occurrences and frequencies of the characteristic data in the historical fault text data, and to distinguish the number of occurrences and frequencies according to different time periods, and also includes dividing the characteristic data;

[0011] The communication module adopts a wireless networking communication method, and is used to send a communication request to a communication base station matching the preset power grid and a communication base station operator when the characteristic data appears in the text data generated by the preset power grid in the future period;

[0012] The management module is used to record and store the data of the information acquisition module and the analysis module, and to distinguish and store the data of the two;

[0013] A text timing module is used to calculate the time taken to generate the corresponding text data when a preset power grid fault occurs, and divide the time into long time, medium time and short time in a step-by-step manner, and preset a safety threshold based on the long time. When the time taken to generate the corresponding text data of the preset power grid when a fault occurs in a future period exceeds the long time, the system determines that the text data generation is abnormal and issues an early warning, otherwise, no determination is made;

[0014] The data acquisition module is used to collect preset power grid fault features corresponding to the text data generation anomaly, analyze the association rules between the features and the text data generation anomaly, and generate a data model.

[0015] As a preferred solution of the present invention, the information acquisition module divides the historical fault text data into climate disaster fault text data and circuit fault text data, and distinguishes the data features of different types of fault text data, and obtains the most time periods and states generated by different types of fault text data through a clustering algorithm.

[0016] As a preferred solution of the present invention, the clustering algorithm obtains the most relevant data under the climate disaster state in the climate disaster fault text data, and obtains the most relevant data under the circuit fault state in the circuit fault text data, and generates a prediction model at the same time.

[0017] As a preferred solution of the present invention, wherein: the clustering algorithm is a clustering algorithm based on non-overlapping sets, and the initial text data of the preset power grid in the state with the most climate disasters and the state with the most circuit faults is obtained through at least three iterations, and the proportion of the initial text data capacity to the total text data capacity of the state with the most climate disasters and the state with the most circuit faults is calculated.

[0018] As a preferred solution of the present invention, the proportion of the initial text data capacity to the total text data capacity of the most climatic disaster state is calculated according to the following formula:

[0019] Wherein, f represents the total text data capacity of the maximum climate disaster status;

[0020] In the formula, σ represents the initial text data selected after different iterations in the most climate disaster state, σ i represents the initial text data of different data capacities collected for the i-th time, h j represents the initial text data collected during the most climatic disaster state in the jth year;

[0021] The proportion of the initial text data capacity to the total text data capacity of the most circuit fault state is calculated according to the following formula:

[0022] C j =H t ·C j +U i ·C j Among them, C j Representing the initial text data of the jth maximum data capacity collected by the preset power grid under the most circuit fault state;

[0023] In the formula, H t represents the capacity change characteristics of the initial text data collected in the tth time period, and analyzes the circuit fault change characteristics corresponding to the capacity change characteristics, U iRepresents the change in capacity between two adjacent initial text data collected for the ith time.

[0024] As a preferred solution of the present invention, wherein: the analysis module distinguishes the number of occurrences and frequencies according to different time periods, including distinguishing the number of occurrences and frequencies of the characteristic data in units of months or quarters, analyzing and obtaining the patterns of the number of occurrences and frequencies of the characteristic data in different months or quarters, and analyzing the preset power grid fault characteristics corresponding to the patterns.

[0025] As a preferred solution of the present invention, the analysis module uses the maximum difference in capacity between the two initial text data to obtain the change law of the circuit fault, and divides the change law into Among them, the n represents the nth change rule, and the text data changes are obtained according to different change rules, and the text data changes corresponding to the change rules are uploaded to the prediction model, and the prediction model is updated at the same time.

[0026] As a preferred solution of the present invention, wherein: the analysis module uses the text data generated in the text data change data corresponding to the low change degree, medium change degree and high change degree of the circuit fault, and presets the risk threshold based on the text data corresponding to the medium change degree. When the system obtains the fault text data of the preset power grid in the future time period corresponding to the circuit fault with the medium change degree, the system determines that the fault of the preset power grid is showing a trend of continuous deterioration and issues an early warning. Otherwise, no determination is made.

[0027] As a preferred solution of the present invention, the analysis module adopts the Monte Carlo method to sample the text data corresponding to the medium degree of change, determines the preset power grid fault state and performs power grid reliability calculation, and at the same time establishes the network communication frequency and performs risk warning based on the sampling value of the text data corresponding to the medium degree of change using the Monte Carlo method.

[0028] As a preferred solution of the present invention, wherein: the analysis module divides the sampling value data into several evaluation indicators, counts the evaluation indicator data of the preset power grid in the medium variation degree fault, normalizes the data, and calculates the weight of each evaluation indicator.

[0029] In another aspect, the present invention provides a management method based on an automatically optimized wireless communication network management system, comprising the following steps:

[0030] Acquire text data generated by historical faults of a preset power grid, divide the text data generated by the historical faults, and simultaneously acquire a preset power grid operation state corresponding to the fault text data;

[0031] Extracting and analyzing the characteristic data in the historical fault text data, and analyzing the number of occurrences and the frequency of the characteristic data in the historical fault text data, and distinguishing the number of occurrences and the frequency according to different time periods, and dividing the characteristic data;

[0032] Recording and storing the data of the information acquisition module and the analysis module, and storing the data of the two separately;

[0033] When a preset power grid fault occurs, the time taken to generate the corresponding text data is calculated, and the time is divided into long time, medium time and short time in a step-by-step manner. At the same time, a safety threshold is preset based on the long time. When the time taken to generate the corresponding text data of the preset power grid when a fault occurs in the future period exceeds the long time, the system determines that the text data generation is abnormal and issues an early warning. Otherwise, no determination is made.

[0034] Collecting preset power grid fault features corresponding to the text data generation anomaly, analyzing the association between the features and the text data generation anomaly, and generating a data model;

[0035] Record the communication base stations and communication base station operators that match the preset power grid, receive the field data uploaded by the collection and monitoring points, and update the background data at the same time; when the fault text data of the preset power grid is obtained, initiate an information acquisition request for the power grid line fault status to the communication base stations and communication base station operators corresponding to the preset power grid.

[0036] The beneficial effects of the present invention are as follows: the present invention utilizes the fault text data features, performs deep learning analysis on the power grid fault status corresponding to the data features, and predicts and analyzes the fault situation of the power grid by analyzing the changing rules of the text data and transmits it in real time. Then, the fault status occurring during the operation of the power grid is judged according to the acquired real-time text data, which is more conducive to timely emergency repair deployment and daily operation and maintenance management of the power grid according to the mastered fault text data. At the same time, a fault situation prediction matrix can be formed according to the number of occurrences and frequency characteristics of the generated text data according to the clustering algorithm, so as to make early predictions on possible power grid failures and ensure the stable operation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0038] Figure 1 A schematic diagram of the modular structure of an automatically optimized wireless communication network management system according to an embodiment of the present invention;

[0039] Figure 2 A schematic diagram of a method flow of an embodiment of the present invention;

[0040] Figure 3 A schematic diagram of the system logic relationship structure of an embodiment of the present invention;

[0041] Numbers in the figure: 110 - information acquisition module; 120 - monitoring terminal; 130 - data fusion analysis unit; 1301 - analysis module; 1302 - communication module; 1303 - management module; 140 - text timing module; 150 - data acquisition module. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0043] Since the system text data generated by the existing technology is mostly generated and transmitted based on the final fault status, and the text data of the process of causing the fault is difficult to generate and communicate in real time, in this case, the monitoring center will not be able to promptly receive the various fault signals that occur during the operation of the power grid, thereby delaying the judgment of the operating status of the power grid. In extreme cases, it will hinder the emergency repair of the power grid and affect the daily operation and maintenance of the power grid.

[0044] Based on this, the present invention proposes an automatically optimized wireless communication network management system and method, which utilizes the fault text data features, conducts deep learning analysis on the power grid fault status corresponding to the data features, and predicts and analyzes the fault situation of the power grid by analyzing the changing rules of the text data and transmits it in real time. Then, the fault status occurring during the operation of the power grid is judged based on the acquired real-time text data, which is more conducive to timely emergency repair deployment and daily operation and maintenance management of the power grid based on the fault text data mastered.

[0045] The present invention is further described in detail below through embodiments and in conjunction with the accompanying drawings.

[0046] Reference Figures 1 to 3 , is an embodiment of the present invention, which provides an automatically optimized wireless communication network management system, including:

[0047] The information acquisition module 110 is used to acquire text data generated by historical faults of a preset power grid, divide the text data generated by the historical faults, and acquire the preset power grid operation status corresponding to the fault text data;

[0048] It should be noted that in this embodiment, the information acquisition module divides the historical fault text data into climate disaster fault text data and circuit fault text data, and distinguishes the data features of different types of fault text data, and obtains the most time periods and states generated by different types of fault text data through a clustering algorithm;

[0049] Furthermore, the clustering algorithm obtains the most relevant data under the climate disaster state in the climate disaster fault text data, and obtains the most relevant data under the circuit fault state in the circuit fault text data, and generates a prediction model at the same time;

[0050] Among them, climate disaster failures include failures caused by weather conditions such as ice disasters and wind disasters, while circuit failures include circuit failures caused by line short circuits and abnormal voltage and current;

[0051] Specifically, in this embodiment, the clustering algorithm is a clustering algorithm based on disjoint sets, which obtains the initial text data of the preset power grid in the most climate disaster state and the most circuit fault state through at least three iterations, and calculates the proportion of the initial text data capacity to the total text data capacity of the most climate disaster state and the most circuit fault state;

[0052] The proportion of the initial text data capacity to the total text data capacity of the most climate disaster states is calculated according to the following formula:

[0053] Among them, f represents the total text data capacity of the maximum climate disaster status;

[0054] In the formula, σ represents the initial text data selected after different iterations in the most climate disaster states, σ i represents the initial text data of different data capacities collected for the i-th time, h j represents the initial text data collected during the most climatic disaster state in the jth year;

[0055] The proportion of the initial text data capacity to the total text data capacity of the most circuit fault state is calculated according to the following formula:

[0056] C j =H t ·C j +U i ·C j Among them, C jIndicates the initial text data of the jth maximum data capacity collected by the preset power grid under the most circuit fault state;

[0057] In the formula, H t represents the capacity change characteristics of the initial text data collected in the tth time period, and analyzes the circuit fault change characteristics corresponding to the capacity change characteristics, U i Indicates the change in capacity between two adjacent initial text data collected for the i-th time;

[0058] The monitoring terminal 120 is used to record the communication base stations and communication base station operators that match the preset power grid, receive the field data uploaded by the collection monitoring point, and update the background data at the same time; when the fault text data of the preset power grid is obtained, a request for obtaining information on the fault status of the power grid line is initiated to the communication base stations and communication base station operators corresponding to the preset power grid;

[0059] The data fusion analysis unit 130, the data fusion analysis unit responds to the historical fault text data acquired by the information acquisition module 110, and is used to extract and analyze the feature data in the historical fault text data. The data fusion analysis unit 130 includes an analysis module 1301, a communication module 1302, and a management module 1303;

[0060] The analysis module 1301 is used to analyze the occurrence times and frequencies of characteristic data in the historical fault text data, and to distinguish the occurrence times and frequencies according to different time periods, and also includes dividing the characteristic data;

[0061] Based on the above, the analysis module uses the maximum difference in capacity between the two initial text data to obtain the change law of circuit faults and divides the change law into Wherein, n represents the nth change rule, and the text data changes are obtained according to different change rules, and the text data changes corresponding to the change rules are uploaded to the prediction model, and the prediction model is updated at the same time;

[0062] In this embodiment, the analysis module further distinguishes the number of occurrences and frequencies according to different time periods, including distinguishing the number of occurrences and frequencies of characteristic data by month or quarter, analyzing and obtaining the regularity of the number of occurrences and frequencies of characteristic data in different months or quarters, and analyzing the preset power grid fault characteristics corresponding to the regularity;

[0063] Specifically, the feature data is divided into θ1, θ2, ..., θ n , where n represents the nth feature data, and analyzes the fault features corresponding to different feature data, forms a data set from the feature data, and divides the data set into a verification set, a test set, and a training set;

[0064] The communication module 1302 adopts a wireless networking communication method, which is used to send a communication request to the communication base station matching the preset power grid and the communication base station operator when the text data generated by the preset power grid appears characteristic data in the future period;

[0065] The management module 1303 is used to record and store the data of the information acquisition module 110 and the analysis module 1301, and to distinguish and store the data of the two;

[0066] The text timing module 140 is used to calculate the time taken to generate the corresponding text data when a preset power grid fault occurs, and divide the time into long time, medium time and short time in a step-by-step manner. At the same time, a safety threshold is preset based on the long time. When the time taken to generate the corresponding text data when the preset power grid fault occurs in the future period exceeds the long time, the system determines that the text data generation is abnormal and issues an early warning. Otherwise, no determination is made.

[0067] The data acquisition module 150 is used to collect preset power grid fault features corresponding to the text data generation anomaly, analyze the association between the features and the text data generation anomaly, and generate a data model;

[0068] It should be emphasized in this embodiment that the analysis module uses the text data generated corresponding to the low change degree, medium change degree and high change degree of the circuit fault in the text data change data, and presets the risk threshold based on the text data corresponding to the medium change degree. When the system obtains the fault text data of the preset power grid in the future period corresponding to the circuit fault with the medium change degree, the system determines that the fault of the preset power grid is in a continuous deterioration trend and issues an early warning. Otherwise, no determination is made.

[0069] The analysis module uses the Monte Carlo method to sample text data corresponding to a medium degree of change, determines the preset power grid fault state and performs power grid reliability calculations, and at the same time, establishes the network communication frequency and performs risk warnings based on the sampled values ​​of the text data corresponding to a medium degree of change using the Monte Carlo method;

[0070] The analysis module divides the sample value data into several evaluation indicators, calculates the evaluation indicator data of the preset power grid in a medium-variable fault, normalizes the data, and calculates the weight of each evaluation indicator;

[0071] Specifically, the data normalization process adopts the Min-Max normalization method to map the values ​​in the evaluation index data set to the range of [0, 1] to obtain the standard value of the evaluation index data.

[0072] Based on the above, this application utilizes the fault text data features, deep learning analysis of the power grid fault status corresponding to the data features, and by analyzing the changing patterns of the text data, predicts and analyzes the fault situation of the power grid and transmits it in real time. Then, based on the acquired real-time text data, the fault status that occurs during the operation of the power grid is judged, which is more conducive to timely emergency repair deployment and daily operation and maintenance management of the power grid based on the fault text data mastered.

[0073] In combination with the above-mentioned automatic optimization wireless communication network management system, this embodiment also proposes an automatic optimization wireless communication network management method applied to the system, as follows:

[0074] Acquire text data generated by historical faults of a preset power grid, divide the text data generated by the historical faults, and simultaneously acquire the preset power grid operation status corresponding to the fault text data;

[0075] Extract and analyze the characteristic data in the historical fault text data, and analyze the number of occurrences and frequency of the characteristic data in the historical fault text data, and distinguish the number of occurrences and frequency according to different time periods, and divide the characteristic data;

[0076] Record and store the data of the information acquisition module and the analysis module, and store the data of the two separately;

[0077] When a preset power grid fault occurs, the time taken to generate the corresponding text data is calculated, and the time is divided into long time, medium time and short time in a step-by-step manner. At the same time, a safety threshold is preset based on the long time. When the time taken to generate the corresponding text data of the preset power grid in the future period when the fault occurs exceeds the long time, the system determines that the text data generation is abnormal and issues an early warning. Otherwise, no determination is made.

[0078] Collecting preset power grid fault features corresponding to the text data generation anomaly, analyzing the correlation between the features and the text data generation anomaly, and generating a data model;

[0079] Record the communication base stations and communication base station operators that match the preset power grid, receive the field data uploaded by the collection and monitoring points, and update the background data at the same time; when the fault text data of the preset power grid is obtained, initiate an information acquisition request for the power grid line fault status to the communication base stations and communication base station operators corresponding to the preset power grid.

[0080] In summary, the present invention utilizes the fault text data features, deep learning analysis of the power grid fault status corresponding to the data features, and by analyzing the changing rules of the text data, predicts and analyzes the fault situation of the power grid and transmits it in real time, and then judges the fault status occurring during the operation of the power grid according to the acquired real-time text data, which is more conducive to timely emergency repair deployment and daily operation and maintenance management of the power grid according to the mastered fault text data. At the same time, it can also form a fault situation prediction matrix according to the number of occurrences and frequency characteristics of the generated text data according to the clustering algorithm, so as to make early predictions on possible power grid failures and ensure the stable operation of the power grid.

[0081] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. An automatically optimized wireless communication network management system, characterized in that: include: An information acquisition module, used to acquire text data generated by historical faults of a preset power grid, divide the text data generated by the historical faults, and acquire a preset power grid operation state corresponding to the fault text data; The monitoring terminal is used to record the communication base stations and communication base station operators that match the preset power grid, receive the field data uploaded by the collection monitoring point, and update the background data at the same time; when the fault text data of the preset power grid is obtained, a request for obtaining information on the fault status of the power grid line is initiated to the communication base station and the communication base station operator corresponding to the preset power grid; A data fusion analysis unit, which responds to the historical fault text data acquired by the information acquisition module and is used to extract and analyze feature data in the historical fault text data. The data fusion analysis unit includes an analysis module, a communication module, and a management module; The analysis module is used to analyze the number of occurrences and frequencies of the characteristic data in the historical fault text data, and to distinguish the number of occurrences and frequencies according to different time periods, and also includes dividing the characteristic data; The communication module adopts a wireless networking communication method, and is used to send a communication request to a communication base station matching the preset power grid and a communication base station operator when the characteristic data appears in the text data generated by the preset power grid in the future period; The management module is used to record and store the data of the information acquisition module and the analysis module, and to distinguish and store the data of the two; A text timing module is used to calculate the time taken to generate the corresponding text data when a preset power grid fault occurs, and divide the time into long time, medium time and short time in a step-by-step manner, and preset a safety threshold based on the long time. When the time taken to generate the corresponding text data of the preset power grid when a fault occurs in a future period exceeds the long time, the system determines that the text data generation is abnormal and issues an early warning, otherwise, no determination is made; The data acquisition module is used to collect preset power grid fault features corresponding to the text data generation anomaly, analyze the association rules between the features and the text data generation anomaly, and generate a data model.

2. The automatic optimization wireless communication network management system according to claim 1, characterized in that: The information acquisition module divides the historical fault text data into climate disaster fault text data and circuit fault text data, distinguishes data features of different types of fault text data, and obtains the most time periods and states generated by different types of fault text data through a clustering algorithm.

3. The automatic optimization wireless communication network management system according to claim 2, characterized in that: The clustering algorithm obtains the most relevant data under the climate disaster state in the climate disaster fault text data, and obtains the most relevant data under the circuit fault state in the circuit fault text data, and generates a prediction model at the same time.

4. The automatic optimization wireless communication network management system according to claim 3, characterized in that: The clustering algorithm is a clustering algorithm based on disjoint sets, which obtains the initial text data of the preset power grid in the state with the most climate disasters and the state with the most circuit faults through at least three iterations, and calculates the proportion of the initial text data capacity to the total text data capacity of the state with the most climate disasters and the state with the most circuit faults.

5. The automatic optimization wireless communication network management system according to claim 4, characterized in that: The proportion of the initial text data capacity to the total text data capacity of the most climate disaster state is calculated according to the following formula: f=σ(σ i ·[h j +f]*h); wherein f represents the total text data capacity of the maximum climate disaster status; In the formula, σ represents the initial text data selected after different iterations in the most climate disaster state, σ i represents the initial text data of different data capacities collected for the i-th time, h j represents the initial text data collected during the most climatic disaster state in the jth year; The proportion of the initial text data capacity to the total text data capacity of the most circuit fault state is calculated according to the following formula: C j =H t ·C j +U i ·C j Among them, C j Representing the initial text data of the jth maximum data capacity collected by the preset power grid under the most circuit fault state; In the formula, H t represents the capacity change characteristics of the initial text data collected in the tth time period, and analyzes the circuit fault change characteristics corresponding to the capacity change characteristics, U i Represents the change in capacity between two adjacent initial text data collected for the ith time.

6. The automatic optimization wireless communication network management system according to claim 1, characterized in that: The analysis module distinguishes the number of occurrences and frequencies according to different time periods, including distinguishing the number of occurrences and frequencies of the characteristic data in units of months or quarters, analyzing and obtaining the regularity of the number of occurrences and frequencies of the characteristic data in different months or quarters, and analyzing the preset power grid fault characteristics corresponding to the regularity.

7. The automatic optimization wireless communication network management system according to claim 4, characterized in that: The analysis module uses the maximum difference in capacity between the two initial text data to obtain the change rule of the circuit fault, and divides the change rule into ▽1, ▽2, ..., ▽ n , wherein n represents the nth change rule, and the text data changes are obtained according to different change rules, and the text data changes corresponding to the change rules are uploaded to the prediction model, and the prediction model is updated at the same time.

8. The automatic optimization wireless communication network management system according to claim 7, characterized in that: The analysis module utilizes the text data generated in the text data change data corresponding to the low degree of change, the medium degree of change and the high degree of change of the circuit fault, and presets a risk threshold based on the text data corresponding to the medium degree of change. When the system obtains the fault text data of the preset power grid in the future time period corresponding to the circuit fault with the medium degree of change, the system determines that the fault of the preset power grid is showing a trend of continuous deterioration and issues an early warning. Otherwise, no determination is made.

9. An automatically optimized wireless communication network management system as claimed in claim 8, characterized in that: The analysis module uses the Monte Carlo method to sample the text data corresponding to the medium degree of change, determines the preset power grid fault state and performs power grid reliability calculation, and at the same time establishes a network communication frequency and performs risk warning based on the sampling value of the text data corresponding to the medium degree of change using the Monte Carlo method.

10. The automatic optimization wireless communication network management system according to claim 9, characterized in that: The analysis module divides the sample value data into a plurality of evaluation indicators, calculates the evaluation indicator data of the preset power grid being in the medium variation degree fault, normalizes the data, and calculates the weight of each evaluation indicator.

11. A management method based on an automatically optimized wireless communication network management system according to claims 1-10, characterized in that: The following steps are involved: Acquire text data generated by historical faults of a preset power grid, divide the text data generated by the historical faults, and simultaneously acquire a preset power grid operation state corresponding to the fault text data; Extracting and analyzing the characteristic data in the historical fault text data, and analyzing the number of occurrences and the frequency of the characteristic data in the historical fault text data, and distinguishing the number of occurrences and the frequency according to different time periods, and dividing the characteristic data; Recording and storing the data of the information acquisition module and the analysis module, and storing the data of the two separately; When a preset power grid fault occurs, the time taken to generate the corresponding text data is calculated, and the time is divided into long time, medium time and short time in a step-by-step manner. At the same time, a safety threshold is preset based on the long time. When the time taken to generate the corresponding text data of the preset power grid when a fault occurs in the future period exceeds the long time, the system determines that the text data generation is abnormal and issues an early warning. Otherwise, no determination is made. Collecting preset power grid fault features corresponding to the text data generation anomaly, analyzing the association between the features and the text data generation anomaly, and generating a data model; Record the communication base stations and communication base station operators that match the preset power grid, receive the field data uploaded by the collection and monitoring points, and update the background data at the same time; when the fault text data of the preset power grid is obtained, initiate an information acquisition request for the power grid line fault status to the communication base stations and communication base station operators corresponding to the preset power grid.

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