Power distribution network high-resistance grounding fault recognition method based on convolutional neural network

A high-resistance ground fault and convolutional neural network technology, applied in the field of distribution network, can solve problems such as threatening the safety of electrical equipment, falling on sandy ground, cement ground, and easy fires, etc., achieving excellent classification performance and adaptability, The effect of enhanced signal comparability and good recognition performance

Inactive Publication Date: 2018-09-07
FUZHOU UNIV
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Problems solved by technology

HIF often exists for a long time. Once the fault current with a small value is not cut off and exists for a long time, it will cause serious harm: the high temperature generated by the fault ignition arc and the contact with combustibles can easily cause fire, threatening the safety of electrical equipment, and high resistance grounding Faults mostly fall on sandy ground, cement ground, etc., which may lead to personal electric shock and other safety accidents. Therefore, it is necessary to quickly detect, identify and classify them, and take corresponding measures

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  • Power distribution network high-resistance grounding fault recognition method based on convolutional neural network
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  • Power distribution network high-resistance grounding fault recognition method based on convolutional neural network

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Embodiment Construction

[0030] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0031] Such as figure 1 As shown, this embodiment provides a method for identifying a high-resistance ground fault in a distribution network based on a convolutional neural network, which specifically includes the following steps:

[0032] Step S1: Obtain transient disturbance signals caused by high-impedance ground faults and other transient conditions;

[0033] Step S2: Decompose the signal obtained in step S1 by using the local feature scale decomposition method;

[0034] Step S3: performing band-pass filtering on the signal decomposed in step S2 according to the set frequency band, and constructing a time-frequency matrix;

[0035] Step S4: Obtain the time spectrum diagram of the block;

[0036] Step S5: Use the convolutional neural network algorithm to classify and identify the block time spectrum diagram obtained in step S4, and then use the BP...

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Abstract

The invention relates to a power distribution network high-resistance grounding fault recognition method based on a convolutional neural network. According to the method, first, a power distribution network high-resistance grounding fault and a three-phase voltage signal and a zero-sequence voltage signal at the low-voltage side of a main transformer under multiple types of transient disturbance are acquired; second, a local feature scale method is utilized to decompose the signals, equal-bandwidth band-pass filtering is performed on all the voltage signals, a time-frequency matrix is constructed, and a block time-frequency spectrum is obtained; and last, a convolutional neural network algorithm is adopted to perform classification and recognition, and whether the high-resistance groundingfault occurs is judged.

Description

technical field [0001] The invention relates to the field of distribution networks, in particular to a method for identifying high-resistance grounding faults in distribution networks based on convolutional neural networks. Background technique [0002] The distribution network is a network that is directly connected to users as the end of the power system to distribute electric energy, including power grids with various voltage levels of 0.4-110kV. The distribution network is the link most closely connected with users in the power system. It covers a wide range of areas and has a higher probability of failure than the transmission network. According to statistics, more than 80% of the failures in the power system occur in the distribution network. At present, the scale of the distribution network continues to expand, and the emphasis on the safety, reliability, and economic operation of the distribution network is also increasing, and the requirements for the safety and rel...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G01R31/02G01R31/08
CPCG01R31/086G01R31/088G01R31/50G06F18/24
Inventor 郭谋发张君琦高伟洪翠杨耿杰
Owner FUZHOU UNIV
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