Detection of inter-turn short-circuit on a Doubly Fed Induction Machine with D-Q axis representation

H. Bilal, N. Héraud, Eric Jean Roy Sambatra
{"title":"Detection of inter-turn short-circuit on a Doubly Fed Induction Machine with D-Q axis representation","authors":"H. Bilal, N. Héraud, Eric Jean Roy Sambatra","doi":"10.1109/RTUCON51174.2020.9316591","DOIUrl":null,"url":null,"abstract":"In this paper, we propose to detect and quantify the fault of inter-turn short-circuit in the winding of a Doubly Fed Induction Machine (DFIM). This is essential to detect this type of defect at an early stage because this one can produce damage to the machine. So, we must be able firstly to detect the fault and secondly to quantify its severity. Our study responds to this and necessities a few calculi. We present in this paper a low sample time (1kHz), and we offer theoretical analysis with a model of our DFIM without fault, and a model included this fault. An analysis of the representation on the D-Q basis is done. After, we confirm these results through the exploitation of a platform which comprises a DFIM and a Data Acquisition (DAQ) system. The obtained results are rather hopeful.","PeriodicalId":332414,"journal":{"name":"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTUCON51174.2020.9316591","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

In this paper, we propose to detect and quantify the fault of inter-turn short-circuit in the winding of a Doubly Fed Induction Machine (DFIM). This is essential to detect this type of defect at an early stage because this one can produce damage to the machine. So, we must be able firstly to detect the fault and secondly to quantify its severity. Our study responds to this and necessities a few calculi. We present in this paper a low sample time (1kHz), and we offer theoretical analysis with a model of our DFIM without fault, and a model included this fault. An analysis of the representation on the D-Q basis is done. After, we confirm these results through the exploitation of a platform which comprises a DFIM and a Data Acquisition (DAQ) system. The obtained results are rather hopeful.
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D-Q轴表示的双馈感应电机匝间短路检测
本文提出了一种双馈感应电机绕组匝间短路故障的检测与量化方法。这对于在早期阶段检测这种类型的缺陷是必不可少的,因为这种缺陷会对机器产生损害。因此,我们首先要能够检测故障,其次要能够量化故障的严重程度。我们的研究回应了这一点,需要一些微积分。本文提出了一个低采样时间(1kHz)的DFIM模型,并对该模型进行了理论分析,该模型包含了该故障。在D-Q的基础上对其表示进行了分析。然后,我们通过开发一个由DFIM和数据采集(DAQ)系统组成的平台来验证这些结果。得到的结果是很有希望的。
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
Measuring the impact of demand response services on electricity prices in Latvian electricity market Case Studies for Optimal Cable Line Placement and Sheath Grounding to Increase its Operational Characteristics Reduction of Electromagnetic Emissions Generated by Inductive Resonant WPT Systems Using Multi-Switching-Frequency-Based Method Economic Assessment Of The Efficiency Of The Application Of Energy Storage System To Compensate The Load Rise And Shedding Of Gas Piston Installation Control Algorithms Based on Load Angle and Phase Current Difference for Traction Switched Reluctance Motor
×
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:481959085
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