• DocumentCode
    2300652
  • Title

    Research on transformer fault diagnosis based on genetic algorithm of ENN

  • Author

    Gong Ruikun ; Lu Fuqiang ; Wang Xinze

  • Author_Institution
    Coll. of Electr. Eng., HeBei United Univ. Tangshan, Tangshan, China
  • fYear
    2012
  • fDate
    29-31 Dec. 2012
  • Firstpage
    834
  • Lastpage
    837
  • Abstract
    For the characteristics of transformer fault diagnosis, this paper puts forward a method based on genetic algorithm and extension neural network power transformer fault diagnosis methods. This paper introduces the double right extension neural network structure; and structure based on genetic algorithm and extension neural network fault diagnosis model and algorithm design, and its application to the diagnosis of power transformer identification; Through the simulation experiment shows the method is simple, training error is small, fast convergence time etc.
  • Keywords
    fault diagnosis; genetic algorithms; neural nets; power engineering computing; power transformers; ENN; extension neural network power transformer fault diagnosis method; genetic algorithm; power transformer identification; right extension neural network structure; extension neural network; genetic algorithm; transformer fault diagnosis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-4673-2963-7
  • Type

    conf

  • DOI
    10.1109/ICCSNT.2012.6526059
  • Filename
    6526059