An ECT-PCA-based Fault Detection Method for Winding Asymmetry of Marine Current Turbine Generator

Tao Xie, Tianzhen Wang
{"title":"An ECT-PCA-based Fault Detection Method for Winding Asymmetry of Marine Current Turbine Generator","authors":"Tao Xie, Tianzhen Wang","doi":"10.1109/DDCLS52934.2021.9455477","DOIUrl":null,"url":null,"abstract":"The traditional detection methods of motor winding asymmetry often analyze the zero-sequence component. However, due to the different types of motors, the collection methods are also different. The marine current turbine (MCT) has a complicated sealing method due to the harsh marine environment, and its working conditions are frequently changed by the influence of the marine current flow rate, which makes it challenging to extract the fault characteristics. This paper proposes a novel method, called ECT-PCA, to detect MCT generator winding asymmetry, which includes: acquiring the stator three-phase current and using the extended Concordia transform (ECT) to obtain the modulus signal; dividing the modulus signal into an equal-length sample, and performing Fourier transform to obtain the frequency domain amplitude; Then establishing a PCA fault detection model, finally uses T2 and SPE statistics to detect whether the winding asymmetry or not. An experimental platform based on the MCT prototype was built to verify the effectiveness of the proposed method.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DDCLS52934.2021.9455477","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The traditional detection methods of motor winding asymmetry often analyze the zero-sequence component. However, due to the different types of motors, the collection methods are also different. The marine current turbine (MCT) has a complicated sealing method due to the harsh marine environment, and its working conditions are frequently changed by the influence of the marine current flow rate, which makes it challenging to extract the fault characteristics. This paper proposes a novel method, called ECT-PCA, to detect MCT generator winding asymmetry, which includes: acquiring the stator three-phase current and using the extended Concordia transform (ECT) to obtain the modulus signal; dividing the modulus signal into an equal-length sample, and performing Fourier transform to obtain the frequency domain amplitude; Then establishing a PCA fault detection model, finally uses T2 and SPE statistics to detect whether the winding asymmetry or not. An experimental platform based on the MCT prototype was built to verify the effectiveness of the proposed method.
基于ect - pca的海流汽轮发电机绕组不对称故障检测方法
传统的电机绕组不对称检测方法往往分析零序分量。但是,由于电机的类型不同,收集方法也不同。由于海洋环境恶劣,海流涡轮(MCT)的密封方法复杂,其工作状态经常受到海流流量的影响,这给故障特征的提取带来了挑战。本文提出了一种新的检测MCT发电机绕组不对称性的方法——ECT- pca,该方法包括:获取定子三相电流,利用扩展的Concordia变换(ECT)得到模量信号;将模数信号分成等长样本,进行傅里叶变换得到频域幅值;然后建立主成分分析故障检测模型,最后利用T2和SPE统计量检测绕组是否不对称。建立了基于MCT原型的实验平台,验证了该方法的有效性。
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