Detection Method of Series Arcing Fault Based on Wavelet Transform and Singular Value Decomposition

被引：0

作者：

Lu Q. ^{[1
]}

Wang T. ^{[1
]}

Li Z. ^{[1
]}

Wang C. ^{[1
]}

机构：

[1] School of Mechanical Electronic and Information Engineering, China University of Mining and Technology(Beijing), Beijing

来源：

Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | 2017年 / 32卷 / 17期

关键词：

Arcing fault; Characteristic parameters; Detection; Singular value decomposition; Wavelet transform;

D O I：

10.19595/j.cnki.1000-6753.tces.170196

中图分类号：

学科分类号：

摘要：

Wavelet transform was a commonly used method to detect the arcing fault according to the change of the current signal in the circuit. However, it was not easy to distinguish the normal condition from arcing fault when simply using wavelet transform, and there was a lot of redundancy in the results. In order to solve this problem, a new detection method of series arcing fault which based on wavelet transform and singular value decomposition is proposed. An arc generator is used to generate series arcing fault, currents in normal condition and arcing fault are collected under multiple loads. Discrete wavelet transform is firstly used in the collected current signal, and the discrete wavelet coefficient sequence is obtained. Then, based on singular value decomposition of characteristic matrix, the characteristic parameters of current signal are defined and used as the basis of the series arcing fault detection. The experimental results show that it is easy to distinguish the characteristic parameters and there is no cross under normal condition and series arcing fault, thus it is easy to determine the threshold value. The accuracy of the series arcing fault detection is high, and the redundancy of the wavelet transform is greatly compressed. © 2017, The editorial office of Transaction of China Electrotechnical Society. All right reserved.

引用

页码：208 / 217

页数：9

共 22 条

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