Arc Fault and Flash Signal Analysis in DC Distribution Systems Using Wavelet Transformation
Arc Fault and Flash Signal Analysis in DC Distribution Systems Using Wavelet Transformation
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DOI：
10.1109/tsg.2015.2407868
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发表时间：
2015-03
影响因子：
9.6
通讯作者：
Zhan Wang;R. Balog
中科院分区：
文献类型：
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作者：
Zhan Wang;R. Balog
电弧故障一直是电气系统的关注点，因为它们可以引起火灾、人员电击危险和系统故障。依赖于时域中的模式识别或使用傅立叶变换的频域分析的现有商业化技术不能很好地工作，因为信噪比低并且电弧信号不是周期性的。相反，小波变换（WT）提供了一个时间和频率的方法来分析目标信号的多分辨率。本文提出了一种基于小波变换的直流系统电弧故障分析新方法。检测电弧故障的过程包括信号分析和特征识别。本文的重点是前者。仿真模型合成研究所提出的方法和传统的快速傅立叶变换分析的电弧故障的理论结果。光伏阵列直流系统的实验数据也验证了这种方法。
Arc faults have always been a concern for electrical systems, as they can cause fires, personnel shock hazard, and system failure. Existing commercialized techniques that rely on pattern recognition in the time domain or frequency domain analysis using a Fourier transform do not work well, because the signal-to-noise ratio is low and the arc signal is not periodic. Instead, wavelet transform (WT) provides a time and frequency approach to analyze target signals with multiple resolutions. In this paper, a new approach using WT for arc fault analysis in dc systems is proposed. The process of detecting an arc fault involves signal analysis and then feature identification. The focus of this paper is on the former. Simulation models are synthesized to study the theoretical results of the proposed methodology and traditional fast Fourier transform analysis on arcing faults. Experimental data from the dc system of a photovoltaic array is also shown to validate the approach.