电网技术Issue(3)：795-801,7.DOI:10.13335/j.1000-3673.pst.2014.03.038
基于多特征融合的交流系统串联电弧故障诊断
Multi-Feature Fusion Based Diagnosis of Series Arc Faults in AC System
摘要
Abstract
To diagnose series arc faults occurred in low-voltage side at power utilization system accurately, according to three features of low-voltage series arc fault signals, namely the singularity, the uncertainty and the energy features, in AC power system and based on simulation experiment results of series arc faults under different loads carried out by the self-constructed experimental platform, a multi-feature fusion based series arc fault diagnosis method is proposed. According to the three features of signal and combining with wavelet transform theory, the proposed method performs principal component analysis (PCA) for sampled signals, whose noise is preprocessed and extracts contribution rates of different frequency bands to signal, then taking the spatial relations among frequency bands where the maximum contribution rates of the three features of the signal locate as the characteristic vectors, a 1×3 order signal features distribution matrix is constituted;taking this matrix as the input vector of improved multi-level BP neural network, using this neural network the mapping relation between characteristic vector and series arc fault is established. Test results show that using the proposed method the impact of burning arc on diagnosis result can be reduced and the diagnosis classification of series arc faults can be realized.关键词
电弧故障/小波变换/多特征融合/故障诊断/神经网络Key words
arc fault/wavelet transform/multi-feature fusion/fault diagnosis/neural network分类
信息技术与安全科学引用本文复制引用
刘晓明,赵洋,曹云东,侯春光..基于多特征融合的交流系统串联电弧故障诊断[J].电网技术,2014,(3):795-801,7.基金项目
国家自然科学基金项目(51377106，51337001)。@@@@Project Supported by National Natural Science Foundation of China(51377106，51337001)． （51377106，51337001）
