Abstract：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.
卢其威, 王涛, 李宗睿, 王聪. 基于小波变换和奇异值分解的串联电弧故障检测方法[J]. 电工技术学报, 2017, 32(17): 208-217.
Lu Qiwei, Wang Tao, Li Zongrui, Wang Cong. Detection Method of Series Arcing Fault Based on Wavelet Transform and Singular Value Decomposition. Transactions of China Electrotechnical Society, 2017, 32(17): 208-217.
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2017, Vol. 32 
