• DocumentCode
    1677532
  • Title

    A hybrid intelligent system for fault detection in power systems

  • Author

    Mori, Hiroyuki ; Aoyama, Hikaru ; Yamanaka, Toshiyuki ; Urano, Shoichi

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Meiji Univ., Kawasaki, Japan
  • Volume
    3
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    2138
  • Lastpage
    2143
  • Abstract
    This paper proposes a method for fault detection with a preconditioned artificial neural network. The proposed method makes use of FFT and deterministic annealing (DA) clustering as a precondition technique. The proposed method is tested in a sample system
  • Keywords
    fast Fourier transforms; knowledge based systems; multilayer perceptrons; pattern clustering; power system analysis computing; power system faults; simulated annealing; DA clustering; FFT; deterministic annealing clustering; fault detection; hybrid intelligent system; power systems; preconditioned artificial neural network; Artificial neural networks; Circuit faults; Control systems; Electrical fault detection; Hybrid intelligent systems; Hybrid power systems; Power system control; Power system faults; Power system planning; Power system security;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7278-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2002.1007472
  • Filename
    1007472