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
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;
Conference_Titel :
Fuzzy Information Processing Society, 2002. Proceedings. NAFIPS. 2002 Annual Meeting of the North American
Print_ISBN :
0-7803-7461-4
DOI :
10.1109/NAFIPS.2002.1018091
