• DocumentCode
    1644078
  • Title

    Pattern recognition of PD in large turbine generators with a neural network system

  • Author

    Wu, Guangning ; Xie, Hengkun ; Ma, Hui ; Jiang, Xiongwei ; Chen, Zhiqing ; Sun, Delin

  • Author_Institution
    Xi´´an Jiaotong Univ., China
  • Volume
    1
  • fYear
    1997
  • Firstpage
    252
  • Abstract
    In this paper, a neural network system used for pattern recognition of partial discharge (PD) is described. The neural network is a three-layer artificial neural system with feed forward connections, and its learning method is back propagation algorithm incorporating with an external teacher signal. Digital PD pulse signal can be obtained by a PD pulse digitized record system. Combination of the discharge magnitude, the phase angle of applied voltage at which PD occurs, and the numbers of pulse counts are taken as the input of the neural network system. After learning typical input patterns, the neural network may discriminate unknown patterns successfully. Some new results are given, and practical application of neural network for pattern recognition of PD in large turbine generators is also discussed
  • Keywords
    backpropagation; feedforward neural nets; insulation testing; machine insulation; machine testing; partial discharges; pattern recognition; turbogenerators; backpropagation algorithm; digital PD pulse signal; external teacher; learning; partial discharge; pattern recognition; three-layer feed-forward artificial neural network; turbine generator; Dielectrics and electrical insulation; Intelligent networks; Multilayer perceptrons; Neural networks; Partial discharge measurement; Partial discharges; Pattern recognition; Power generation; Turbines; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Properties and Applications of Dielectric Materials, 1997., Proceedings of the 5th International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    0-7803-2651-2
  • Type

    conf

  • DOI
    10.1109/ICPADM.1997.617575
  • Filename
    617575