Broken rotor bar detection in VSD-fed induction motors at startup by high-resolution spectral analysis

R. Romero-Troncoso, D. Morinigo-Sotelo, Ó. Duque-Pérez, R. Osornio-Rios, M. Ibarra-Manzano, A. García-Perez
{"title":"Broken rotor bar detection in VSD-fed induction motors at startup by high-resolution spectral analysis","authors":"R. Romero-Troncoso, D. Morinigo-Sotelo, Ó. Duque-Pérez, R. Osornio-Rios, M. Ibarra-Manzano, A. García-Perez","doi":"10.1109/ICELMACH.2014.6960435","DOIUrl":null,"url":null,"abstract":"The fault detection in an induction motor (IM) operated by a variable speed drive (VSD) is an actual industrial need as most of the line-fed machines are replaced by a VSD, due to their improved speed regulation and fast dynamic response. However, undesired harmonics are always present when the IM is fed through a VSD. Under this operating condition, most developed techniques are unable to detect faults in the IM. This paper presents a technique based on the multiple signal classification (MUSIC) method, and it is applied to a VSD-fed IM during the startup transient; in order to verify the capability of the method to identify one broken rotor bar. From the experimental results, the proposed method is proven to be sensitive enough to detect one broken rotor bar, enabling a reliable diagnosis under different fundamental supply frequencies and load conditions.","PeriodicalId":288960,"journal":{"name":"2014 International Conference on Electrical Machines (ICEM)","volume":"146 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Electrical Machines (ICEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICELMACH.2014.6960435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18

Abstract

The fault detection in an induction motor (IM) operated by a variable speed drive (VSD) is an actual industrial need as most of the line-fed machines are replaced by a VSD, due to their improved speed regulation and fast dynamic response. However, undesired harmonics are always present when the IM is fed through a VSD. Under this operating condition, most developed techniques are unable to detect faults in the IM. This paper presents a technique based on the multiple signal classification (MUSIC) method, and it is applied to a VSD-fed IM during the startup transient; in order to verify the capability of the method to identify one broken rotor bar. From the experimental results, the proposed method is proven to be sensitive enough to detect one broken rotor bar, enabling a reliable diagnosis under different fundamental supply frequencies and load conditions.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于高分辨率光谱分析的vsd异步电动机启动时转子断条检测
变速驱动(VSD)驱动的感应电机(IM)故障检测是一种实际的工业需求,因为大多数直线进给机器都被VSD取代,因为它们具有改进的调速和快速的动态响应。然而,当通过VSD馈送IM时,总是存在不希望的谐波。在这种工作条件下,大多数现有的技术都无法检测到IM中的故障。本文提出了一种基于多信号分类(MUSIC)方法的技术,并将其应用于vsd馈电IM的启动瞬态;为了验证该方法对转子断条的识别能力。实验结果表明,该方法具有足够的灵敏度,可以检测到转子断条,在不同的基频供电频率和负载条件下都能进行可靠的诊断。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Thermal performance analysis of the double-sided linear switched reluctance motor Brushless Doubly-Fed Induction Machines: Magnetic field modelling Demagnetization faults analysis in a BLDC motor for diagnostic purposes Iron loss and parameter measurement of permanent magnet synchronous machines Synchronous reluctance machine flux barrier design based on the flux line patterns in a solid rotor
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1