Fault detection in large AC machines

S. Foda, M. Abdel-Rahman, K. E. Addoweesh
{"title":"Fault detection in large AC machines","authors":"S. Foda, M. Abdel-Rahman, K. E. Addoweesh","doi":"10.1109/ICM.2001.997520","DOIUrl":null,"url":null,"abstract":"The emerging techniques of artificial neural networks (ANNs) are applied to the problem of developing an artificial neural system capable of detecting interlayer faults in large AC machines using line-end coil voltage measurements. The proposed ANN system is a two-layer back propagation neural network, which is basically a classifier capable of recognizing data vectors buried in noise. The developed ANN system is fast to train and produced reliable fault detection and localization with noisy measurements. Furthermore, the proposed system needs neither data pre-processing nor feature extraction networks.","PeriodicalId":360389,"journal":{"name":"ICM 2001 Proceedings. The 13th International Conference on Microelectronics.","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICM 2001 Proceedings. The 13th International Conference on Microelectronics.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICM.2001.997520","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The emerging techniques of artificial neural networks (ANNs) are applied to the problem of developing an artificial neural system capable of detecting interlayer faults in large AC machines using line-end coil voltage measurements. The proposed ANN system is a two-layer back propagation neural network, which is basically a classifier capable of recognizing data vectors buried in noise. The developed ANN system is fast to train and produced reliable fault detection and localization with noisy measurements. Furthermore, the proposed system needs neither data pre-processing nor feature extraction networks.
大型交流电机故障检测
将人工神经网络(ann)的新兴技术应用于开发一种能够通过测量线端线圈电压来检测大型交流电机层间故障的人工神经系统。所提出的人工神经网络系统是一个双层反向传播神经网络,它基本上是一个能够识别隐藏在噪声中的数据向量的分类器。所开发的人工神经网络系统训练速度快,能够在噪声测量下进行可靠的故障检测和定位。此外,该系统不需要数据预处理,也不需要特征提取网络。
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:604180095
Book学术官方微信