基于滑动离散傅里叶变换的串联直流电弧故障识别

doi:10.19595/j.cnki.1000-6753.tces.161082

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Abstract Series DC arcing fault pose an extreme safety risk in DC power system because it is difficult to be detected. A sliding discrete fourier transform (DFT) based arcing fault recognition method is proposed to meet the requirement of real-time in detection and reduction in algorithm complexity. The arcing initiation stage is the best moment for fault detection based on analysis both in time domain and in frequency domain. Accordingly, three characteristic frequencies, 40 kHz, 80 kHz and 100 kHz, are selected for the point by point sliding DFT calculation. Moreover, a time-window of 200μs is used to implement the algorithm for simplicity and accuracy. Finally, it is concluded that all the three spectrums increase significantly during the arcing fault. And the sliding DFT algorithm can be applied for series DC arcing fault recognition.

Key words： Series DC arcing arcing fault fault detection sliding discrete fourier transform

Received: 13 July 2016 Published: 25 October 2017

PACS:

TM501

Corresponding Authors: 国家自然科学基金（51607055）、河北省自然科学基金（E2015202143）和河北省教育厅青年科学基金（QN2014148）资助项目

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	Wang Yao
	Li Yang
	Ge Leijiao
	Niu Feng
	Li Kui

Cite this article:

Wang Yao,Li Yang,Ge Leijiao等. A Series DC Arcing Fault Recognition Method Based on Sliding Discrete Fourier Transform[J]. Transactions of China Electrotechnical Society, 2017, 32(19): 118-124.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.161082 OR https://dgjsxb.ces-transaction.com/EN/Y2017/V32/I19/118

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