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Electric power communication network fault analysis and positioning method based on convolutional neural network

A technology of convolutional neural network and power communication network, which is applied in the field of fault analysis and location of power communication network based on convolutional neural network, can solve problems such as difficulty in diagnosing faults and insufficient types of fault samples, and achieve enhanced relevance and change adaptation Ability to improve the effect of multiple features

Active Publication Date: 2020-03-31
国网湖北省电力有限公司信息通信公司
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AI Technical Summary

Problems solved by technology

However, when the network topology is very complex and numerous, and the types of marked fault samples are insufficient, it is difficult to diagnose faults among numerous alarm information

Method used

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Embodiment Construction

[0016] The power communication network fault analysis and location method based on convolutional neural network is characterized in that, comprising the following steps:

[0017] (1) Obtain the alarm information of each professional network management, obtain the original alarm information database, select the alarm information fields with high importance to fault diagnosis and standardize the data, such as selecting the alarm level, alarm name, alarm type, start time, There are five important fields for positioning information. The data in the target alarm database is synchronized with the site using a time window. The size of the time window is represented by W. The size of W can be considered as the maximum time interval related to two alarm transactions. The alarm information of the same time window belongs to one alarm business; use formula To calculate the impact weight of each alarm type on the final fault diagnosis, where alarm A is the abbreviation of the alarm, wA ...

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Abstract

The invention relates to an electric power communication network fault analysis and positioning method based on a convolutional neural network. The method is mainly used for feature diagnosis of alarmdata and a network topology structure in an electric power communication network. Keyword selection and standardization are carried out on alarm information, synchronous processing is carried out toobtain alarm transaction data, and weighted encoding is carried out on the alarm transaction data and a network adjacent matrix to obtain a fault state matrix containing a network topology connectionrelationship and a network fault state. According to the method, the network topology connection relationship and the alarm information are mapped into the fault state matrix, so that multiple characteristics required by fault diagnosis are improved, and meanwhile, the network topology information is combined, so that the relevance and change adaptability of the network are enhanced.

Description

technical field [0001] The invention relates to a power communication network fault analysis and positioning method, in particular to a power communication network fault analysis and positioning method based on a convolutional neural network. Background technique [0002] Nowadays, the development of any country is inseparable from the role of the power system. Many countries are doing research on smart grids in order to use grid resources more efficiently and rationally. The power communication network is the neural network of the power system, which plays a vital monitoring and control task for the entire power system. It connects all aspects of the power system and is responsible for the transmission, production and management of information. It is an important infrastructure of the power system. Once the network fails, it is very important to diagnose the fault accurately and timely. However, with the rapid development of the power communication network, its network sca...

Claims

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Application Information

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IPC IPC(8): H04L12/24G06N3/04
CPCH04L41/0677H04L41/0604H04L41/0631H04L41/145H04L41/142H04L41/12G06N3/045Y04S10/52
Inventor 杨杉肖治华张成郭峰张岱柯旺松齐放姚渭箐胡晨
Owner 国网湖北省电力有限公司信息通信公司
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