基于WPD-SVD的串联故障电弧检测方法  

Series Arc Fault Detection Method Based on WPD-SVD

作　　者：王泽伦 李夏 郭琎 陶森翼 王海南 WANG Zelun;LI Xia;GUO Jin;TAO Senyi;WANG Hainan(CCTEG China Coal Research Institute,Beijing 100013,China;Engineering Research Center for Technology Equipment of Emergency Refuge in Coal Mine,Beijing 100013,China;Beijing Mine Safety Engineering Technology Research Center,Beijing 100013,China)

机构地区：[1]煤炭科学技术研究院有限公司,北京100013 [2]煤矿应急避险技术装备工程研究中心,北京100013 [3]北京市煤矿安全工程技术研究中心,北京100013

出　　处：《电工技术》2023年第15期1-5,共5页Electric Engineering

基　　金：煤炭科学技术研究院有限公司科技发展基金项目“矿用监控监测系统智能运维技术研究”(编号2022CX-I-07);煤炭科学技术研究院有限公司新产品新工艺开发项目“基于自动化包装设备的一体化产线”(编号2022CG-ZB-19)。

摘　　要：为了研究电力系统中串联故障电弧检测问题,以三相交流电机为例,设计了一种基于小波包-奇异值分解的串联故障电弧检测方法。首先,进行了串联故障电弧实验,获得了电机A相电流数据;其次,对电流数据进行小波包分解及进一步的奇异值分解,并成功提取特征值;最终,进行6个组别各50次重复实验并将重复实验结果平均处理,再对同组前4个特征值进行加权平均处理,获得WPD-SVD判别标准特征值。在进行正常与故障状态特征值对比后,证明特征值间距及稳定性都较为理想,足够作为串联故障电弧检测判据。In order to study series arc fault detection in power system,using a three-phase AC motor as an example,a method based on wavelet packet decomposition-singular value decomposition is designed.Firstly,the series arc fault experiment is carried out,and the motor A-phase current data is obtained.Secondly,the wavelet packet decomposition and further singular value decomposition are performed,and the characteristics are successfully extracted.Finally,50 replicate experiments are performed for each of the 6 groups and the results of duplicate experiments are averaged,and subsequently the first 4 characteristics of the same group are treated by a weighted average.After comparing the characteristic values between normal and abnormal state,it is proved that the characteristics spacing and stability are relatively ideal,which is sufficient to serve as detection criterion for the series arc fault.

关 键 词：串联故障电弧 负载电流 小波包分解 奇异值分解 特征值 

分 类 号：TM501[电气工程—电器]