DocumentCode
1957751
Title
Application of fuzzy logic pattern recognition in load tap changer transformer maintenance
Author
Rastgoufard, Parviz ; Petry, Frederick ; Thumm, Brian ; Montgomery, Melinda
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Tulane Univ. Sch. of Eng., New Orleans, LA, USA
fYear
2002
fDate
2002
Firstpage
389
Lastpage
394
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.
Keywords
fuzzy logic; maintenance engineering; pattern recognition; transformers; Hard C-Mean; clustering; electric power industry; equipment maintenance monitoring; fuzzy C-Mean; fuzzy logic; load tap changer; pattern recognition; substation maintenance; Application software; Fuzzy logic; Maintenance; Pattern recognition; Samarium; Springs; Stress; Substations; Vibration measurement; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 2002. Proceedings. NAFIPS. 2002 Annual Meeting of the North American
Print_ISBN
0-7803-7461-4
Type
conf
DOI
10.1109/NAFIPS.2002.1018091
Filename
1018091
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