• DocumentCode
    2097581
  • Title

    Evaluation of electrical insulation using genetically evolved artificial neural nets

  • Author

    Wahidabanu, R.S.D. ; Selvam, M. A Panneer ; Udayakumar, K.

  • Author_Institution
    Anna Univ., Madras, India
  • fYear
    1997
  • fDate
    22-25 Sep 1997
  • Firstpage
    279
  • Lastpage
    282
  • Abstract
    The degree of electrical insulation degradation depends strongly on the insulation´s defects. Different types of insulation defects generate different partial discharge (PD) patterns. The correlation that exists between a defect and its pattern is identified and recognized by popular artificial neural nets (ANN) as they significantly improve the recognition of complex patterns in noisy data. An evolutionary design concept is used to realize such an ANN, to avoid the problem of stagnation, and satisfactory results are obtained
  • Keywords
    automatic test software; data acquisition; electric breakdown; insulation testing; neural nets; partial discharges; pattern recognition; breakdown testing; complex pattern recognition; electrical insulation; evolutionary design concept; genetically-evolved artificial neural nets; insulation defects; noisy data; partial discharge; testing automation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Insulation Conference, 1997, and Electrical Manufacturing & Coil Winding Conference. Proceedings
  • Conference_Location
    Rosemont, IL
  • ISSN
    0362-2479
  • Print_ISBN
    0-7803-3959-2
  • Type

    conf

  • DOI
    10.1109/EEIC.1997.651095
  • Filename
    651095