Transformer fault diagnostic method based on gray fuzzy firefly algorithm optimization

A technology of transformer fault and firefly algorithm, applied in instruments, scientific instruments, measurement of electrical variables, etc., can solve the problems of lack of data sources of transformer fault gas and low accuracy of results.

Active Publication Date: 2014-04-02
西安金源电气股份有限公司
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Problems solved by technology

[0004] The purpose of the present invention is to provide a transformer fault diagnosis method based on gray fuzzy firefly algorithm optimization, which solves the problems of lack of transformer fault gas data sources and low accuracy of results in existing analysis methods

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  • Transformer fault diagnostic method based on gray fuzzy firefly algorithm optimization
  • Transformer fault diagnostic method based on gray fuzzy firefly algorithm optimization
  • Transformer fault diagnostic method based on gray fuzzy firefly algorithm optimization

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Embodiment Construction

[0131] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0132] The transformer fault diagnosis method based on gray fuzzy firefly algorithm optimization of the present invention, such as figure 1 As shown, the specific steps are as follows:

[0133] Step 1. First use the characteristic gas content prediction module to select the effective data sequence of the five characteristic gas contents of the transformer, and then use the univariate time series gray model GM (1, 1) to obtain the characteristics of the original transformer five characteristic gas independent variable sequences at the next moment Gas Predicted Values:

[0134] Step 1.1, using the characteristic gas content prediction module to select five characteristic gases of the transformer, these five characteristic gases are: methane, hydrogen, ethane, ethylene, acetylene;

[0135] Since the large amount of transformer characteristic g...

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Abstract

The invention discloses a transformer fault diagnostic method based on gray fuzzy firefly algorithm optimization. The method comprises the following steps: effective data sequences of the contents of five characteristic gases of a transformer are selected through a characteristic gas content prediction module, and the characteristic gas predictive values at a time under the independent variable sequences of the five characteristic gases are obtained through a univariate time sequence gray model; pretreatment is performed on data; characteristic gas coding sequences are used as inputs of training samples, and transformer fault types corresponding to the inputs are used as outputs to built an IGSO-LM network, and the weight value and the threshold value of the LM network are optimized through an IGSO algorithm; the network is trained by using pretreated data of the characteristic gases of the transformer, so as to obtain an optimal nerve net weight value and the threshold value to built a transformer fault diagnostic model and judge the transformer fault types. The transformer fault diagnostic method provided by the invention solves the problems of data source shortage of transformer fault gases and low result accuracy in a conventional analysis method.

Description

technical field [0001] The invention belongs to the technical field of transformer fault online monitoring methods, and in particular relates to a transformer fault diagnosis method optimized based on gray fuzzy firefly algorithm. Background technique [0002] With the development of society, electric power has increasingly become an important part of the national economy, and the rapid development of modern industry and agriculture has put forward higher requirements for power transmission and transformation. In 2009, the State Grid Corporation proposed to build a smart grid with UHV as the backbone grid and coordinated development of power grids at all levels, and the six links of the strategic framework for smart grid development highlighted the importance of power transmission and transformation. The safe and reliable operation of the intelligent substation is one of the main conditions for the stable operation of the entire smart grid, and the intelligent power transfor...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/00G01R31/12G01N33/00G06N3/02
Inventor 黄新波宋桐王娅娜李文君子
Owner 西安金源电气股份有限公司
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