{"title":"Application of fuzzy logic pattern recognition in load tap changer transformer maintenance","authors":"P. Rastgoufard, F. Petry, B. Thumm, M. Montgomery","doi":"10.1109/NAFIPS.2002.1018091","DOIUrl":null,"url":null,"abstract":"The purpose of this investigation is to apply Hard C-Mean (HCM) and Fuzzy C-Mean (FCM) rules in clustering data sets that correspond to different Load Tap Changer (LTC) contact conditions. The stress exerted on the moving arm of a LTC is measured and is then converted to a voltage output signal. It is shown that as the LTC contact conditions deteriorate, the repetitive patterns of the output signal changes correspondingly. The HCM, FCM, and their validity measures prove to be suitable tools for online equipment maintenance monitoring.","PeriodicalId":348314,"journal":{"name":"2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2002.1018091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The purpose of this investigation is to apply Hard C-Mean (HCM) and Fuzzy C-Mean (FCM) rules in clustering data sets that correspond to different Load Tap Changer (LTC) contact conditions. The stress exerted on the moving arm of a LTC is measured and is then converted to a voltage output signal. It is shown that as the LTC contact conditions deteriorate, the repetitive patterns of the output signal changes correspondingly. The HCM, FCM, and their validity measures prove to be suitable tools for online equipment maintenance monitoring.
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