基于几种算法融合的电力电容器局部放电信号提取方法

Huang Zhi-chao, Yan Hong-yan, Fan Xing-ming, Yang Sheng-zhen, Li Zhen, Liang Cong
{"title":"基于几种算法融合的电力电容器局部放电信号提取方法","authors":"Huang Zhi-chao, Yan Hong-yan, Fan Xing-ming, Yang Sheng-zhen, Li Zhen, Liang Cong","doi":"10.1109/DEIV.2012.6412470","DOIUrl":null,"url":null,"abstract":"Partial discharge (PD) is the initial sign of power capacitor insulation failure, and an effective extraction and analysis method of PD signal in power capacitor can improve the effectiveness of the on-line fault monitoring. The method which based on wavelet threshold denoising and mathematical morphology alternate mixing filter is put forward in this paper. First, the PD signal which includes noise is wavelet decomposed with the proper wavelet function and scale, and each layer of wavelet coefficients is extracted. Then appropriate flat structure element is chosen aimed at the scales of wavelet coefficients, and the mathematical morphology alternate mixing filter is used to filter out the noise and get a new wavelet coefficients. Choosing the appropriate threshold rules for the new wavelet coefficients, the wavelet coefficients after the threshold treatment is wavelet reconstructed and the PD signal after denoising is got. The wave distortion mean square error eMSE and SNR are chosen as the indicators to analyze and compare the denoising effects of wavelet threshold denoising method and the fusion denoising method. The results show that the fusion method can effectively remove the noise and keep the original shape characteristic of the signal better.","PeriodicalId":130964,"journal":{"name":"2012 25th International Symposium on Discharges and Electrical Insulation in Vacuum (ISDEIV)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The method of power capacitor partial discharge signal extraction based on several algorithms fusion\",\"authors\":\"Huang Zhi-chao, Yan Hong-yan, Fan Xing-ming, Yang Sheng-zhen, Li Zhen, Liang Cong\",\"doi\":\"10.1109/DEIV.2012.6412470\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Partial discharge (PD) is the initial sign of power capacitor insulation failure, and an effective extraction and analysis method of PD signal in power capacitor can improve the effectiveness of the on-line fault monitoring. The method which based on wavelet threshold denoising and mathematical morphology alternate mixing filter is put forward in this paper. First, the PD signal which includes noise is wavelet decomposed with the proper wavelet function and scale, and each layer of wavelet coefficients is extracted. Then appropriate flat structure element is chosen aimed at the scales of wavelet coefficients, and the mathematical morphology alternate mixing filter is used to filter out the noise and get a new wavelet coefficients. Choosing the appropriate threshold rules for the new wavelet coefficients, the wavelet coefficients after the threshold treatment is wavelet reconstructed and the PD signal after denoising is got. The wave distortion mean square error eMSE and SNR are chosen as the indicators to analyze and compare the denoising effects of wavelet threshold denoising method and the fusion denoising method. The results show that the fusion method can effectively remove the noise and keep the original shape characteristic of the signal better.\",\"PeriodicalId\":130964,\"journal\":{\"name\":\"2012 25th International Symposium on Discharges and Electrical Insulation in Vacuum (ISDEIV)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 25th International Symposium on Discharges and Electrical Insulation in Vacuum (ISDEIV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DEIV.2012.6412470\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 25th International Symposium on Discharges and Electrical Insulation in Vacuum (ISDEIV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEIV.2012.6412470","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

局部放电是电力电容器绝缘故障的初始信号,有效提取和分析电力电容器局部放电信号可以提高故障在线监测的有效性。提出了一种基于小波阈值去噪和数学形态学交替混合滤波的方法。首先,对含噪声的PD信号进行小波分解,采用合适的小波函数和尺度,提取各层小波系数;然后针对小波系数的尺度选择合适的平面结构单元,利用数学形态学交替混合滤波器滤除噪声,得到新的小波系数。对新的小波系数选择合适的阈值规则,对阈值处理后的小波系数进行小波重构,得到去噪后的PD信号。以波畸变均方误差eMSE和信噪比为指标,分析比较了小波阈值去噪方法和融合去噪方法的去噪效果。结果表明,该融合方法能有效去除噪声,较好地保持了信号的原始形状特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The method of power capacitor partial discharge signal extraction based on several algorithms fusion
Partial discharge (PD) is the initial sign of power capacitor insulation failure, and an effective extraction and analysis method of PD signal in power capacitor can improve the effectiveness of the on-line fault monitoring. The method which based on wavelet threshold denoising and mathematical morphology alternate mixing filter is put forward in this paper. First, the PD signal which includes noise is wavelet decomposed with the proper wavelet function and scale, and each layer of wavelet coefficients is extracted. Then appropriate flat structure element is chosen aimed at the scales of wavelet coefficients, and the mathematical morphology alternate mixing filter is used to filter out the noise and get a new wavelet coefficients. Choosing the appropriate threshold rules for the new wavelet coefficients, the wavelet coefficients after the threshold treatment is wavelet reconstructed and the PD signal after denoising is got. The wave distortion mean square error eMSE and SNR are chosen as the indicators to analyze and compare the denoising effects of wavelet threshold denoising method and the fusion denoising method. The results show that the fusion method can effectively remove the noise and keep the original shape characteristic of the signal better.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信