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基于小波分析的故障电弧检测方法
引用本文:孙鹏,郑志成,高翔.基于小波分析的故障电弧检测方法[J].高压电器,2012,48(1):25-29,34.
作者姓名:孙鹏  郑志成  高翔
作者单位:沈阳工业大学特种电机与高压电器实验室,沈阳,110870
基金项目:辽宁省教育厅科技计划项目
摘    要:为了对配电系统中常见的故障电弧实现快速可靠诊断,进而采取有效的保护措施,笔者提出一种基于多分辨分析的快速小波变换分析提取故障电弧特征频段的诊断方法,利用基于非参数自适应估计理论的Birge-Massart策略进行阀值求解,结合小波阀值降噪解功能对电弧电流进行降噪处理。根据小波分析适于分析非平稳信号的特点,采用该分析方法检测不同类型负载下电弧电流中的奇异信号。综合实验数据,分析表明该方法能有效地实现对故障电弧的诊断。

关 键 词:故障电弧  多分辨分析  小波分析  特征频段  Birge-Massart策略  阀值  非平稳信号  奇异信号

Arc Fault Detection Based on Wavelet Analysis
SUN Peng , ZHENG Zhi-cheng , GAO Xiang.Arc Fault Detection Based on Wavelet Analysis[J].High Voltage Apparatus,2012,48(1):25-29,34.
Authors:SUN Peng  ZHENG Zhi-cheng  GAO Xiang
Affiliation:(Special Motor and High Voltage Apparatus Laboratory,Shenyang University of Technology,Shenyang 110870,China)
Abstract:For the purpose of quick and reliable diagnosis of arc fault which occurs frequently in power distribution system and taking effective protection measures,this paper presents a method of analyzing and extracting the characteristic frequency bands of the arc fault current on the basis of the fast wavelet transform with multiresolution analysis.The signal of arc fault current is denoised using the threshold denoising method combining with Birge-Massart threshold value strategy which is based on the non-parametric adaptive estimation theory.The wavelet decomposition,which is suitable for analyzing non-stationary signals,is adopted to detect the singularity of arc fault currents under different types of load.The analysis combining with experiment data shows this method can detect the arc fault effectively.
Keywords:arc fault  multiresolution analysis  wavelet analysis  characteristic frequency bands  Birge-Massart strategy  threshold  non-stationary signals  singularity signal
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