DWT and BPNN based fault detection, classification and estimation of location of HVAC transmission line

Binoy Saha, Bikash Patel, P. Bera
{"title":"DWT and BPNN based fault detection, classification and estimation of location of HVAC transmission line","authors":"Binoy Saha, Bikash Patel, P. Bera","doi":"10.1109/ICICPI.2016.7859697","DOIUrl":null,"url":null,"abstract":"The paper presents a technique for detection classification and diagnosis of fault location on overhead transmission lines for different types of fault. Discrete wavelet transform (DWT) has been used for extraction of features of signals of current under faulted condition and back propagation neural network (BPNN) have been used for training the features of current signal for different fault location. It has been found that the coefficients of discrete wavelet transform of fault signal and BPNN satisfactorily detect, classify and locate the fault location.","PeriodicalId":6501,"journal":{"name":"2016 International Conference on Intelligent Control Power and Instrumentation (ICICPI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Intelligent Control Power and Instrumentation (ICICPI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICPI.2016.7859697","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

The paper presents a technique for detection classification and diagnosis of fault location on overhead transmission lines for different types of fault. Discrete wavelet transform (DWT) has been used for extraction of features of signals of current under faulted condition and back propagation neural network (BPNN) have been used for training the features of current signal for different fault location. It has been found that the coefficients of discrete wavelet transform of fault signal and BPNN satisfactorily detect, classify and locate the fault location.
基于DWT和BPNN的暖通输电线路故障检测、分类和位置估计
提出了一种针对架空输电线路不同类型故障的检测、分类和故障定位诊断技术。采用离散小波变换(DWT)提取故障状态下的电流信号特征,采用反向传播神经网络(BPNN)训练不同故障定位的电流信号特征。研究发现,故障信号的离散小波变换系数和BPNN能较好地检测、分类和定位故障位置。
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