• 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