Detection of partial discharge signals in high voltage XLPE cables using time domain features

R. Ambikairajah, B. Phung, J. Ravishankar, T. Blackburn, Z. Liu
{"title":"Detection of partial discharge signals in high voltage XLPE cables using time domain features","authors":"R. Ambikairajah, B. Phung, J. Ravishankar, T. Blackburn, Z. Liu","doi":"10.1109/EIC.2011.5996179","DOIUrl":null,"url":null,"abstract":"Almost all cases of insulation degradation in high voltage cables are due to partial discharge (PD) activity. To date, wavelet based analysis has been widely used to extract PD pulses from noisy environments. This paper explores the use of time domain features, namely short-time energy and short-time zero-crossing counts, to detect the presence of partial discharge signals prior to de-noising the signal for further investigation. In order to demonstrate the effectiveness of short-time energy and zero-crossing counts to identify PD signals embedded in noise, these features are tested with laboratory data. To further verify these results, real data was collected from a substation and the overall results demonstrate that these two time domain features are very effective in identifying PD pulses and are computationally efficient such that they can be considered for use in online PD monitoring.","PeriodicalId":129127,"journal":{"name":"2011 Electrical Insulation Conference (EIC).","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Electrical Insulation Conference (EIC).","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIC.2011.5996179","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Almost all cases of insulation degradation in high voltage cables are due to partial discharge (PD) activity. To date, wavelet based analysis has been widely used to extract PD pulses from noisy environments. This paper explores the use of time domain features, namely short-time energy and short-time zero-crossing counts, to detect the presence of partial discharge signals prior to de-noising the signal for further investigation. In order to demonstrate the effectiveness of short-time energy and zero-crossing counts to identify PD signals embedded in noise, these features are tested with laboratory data. To further verify these results, real data was collected from a substation and the overall results demonstrate that these two time domain features are very effective in identifying PD pulses and are computationally efficient such that they can be considered for use in online PD monitoring.
利用时域特征检测高压XLPE电缆局部放电信号
高压电缆中几乎所有的绝缘退化都是由于局部放电(PD)活动引起的。迄今为止,基于小波的分析已被广泛用于从噪声环境中提取PD脉冲。本文探讨了使用时域特征,即短时能量和短时过零计数,在进一步研究信号去噪之前检测局部放电信号的存在。为了证明短时能量和过零计数识别嵌入噪声中的PD信号的有效性,用实验室数据对这些特征进行了测试。为了进一步验证这些结果,从变电站收集了实际数据,总体结果表明,这两个时域特征在识别PD脉冲方面非常有效,并且计算效率很高,因此可以考虑将其用于在线PD监测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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