Application Of Wavelet Transform and MLP Neural Network For Ferroresonance Identification

被引：0

作者：

Mokryani, G. ^{[1
]}

Haghifam, M. -R. ^{[2
]}

机构：

[1] Islamic Azad Univ Ilkhchi, Ilkhchi, Iran

[2] Tarbiat Modarres, Dept Elect Engn, Tehran, Iran

来源：

2008 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, VOLS 1-11 | 2008年

关键词：

MLP neural network; Ferroresonance; EMTP program; Wavelet transform;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

In this paper an efficient method for detection of Ferroresonance in distribution transformer based on wavelet transform is presented. Using this method Ferroresonance can be discriminate from other transients such as capacitor switching, load switching, transformer switching. Wavelet transform is used for decomposition of signals and Multi Layer Perceptron(MLP) neural network used for classification. Ferroresonance data and other transients are obtained by simulation using EMTP program. Results show that the proposed procedure is efficient in identifying Ferroresonance from other transients.

引用

页码：2169 / +

页数：2

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