• DocumentCode
    3180660
  • Title

    Fault diagnosis of power electronic circuits based on neural network and waveform analysis

  • Author

    Ma, Hao ; Xu, Dehong ; Lee, Yim-Shu

  • Author_Institution
    Dept. of Electr. Eng., Zhejiang Univ., Hangzhou, China
  • Volume
    1
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    234
  • Abstract
    Based on neural network theory, a new fault diagnosis method for power electronic circuits is presented. By keeping the relations between faults and waveforms in a neural network, the neural network can be trained to detect faults. So automation of fault diagnosis can be realized. In this paper, the fault diagnosis of a three-phase SCR rectifier circuit will be taken as an example to illustrate the new method. Both simulation and experimental results are given
  • Keywords
    AC-DC power convertors; circuit analysis computing; fault diagnosis; learning (artificial intelligence); neural nets; power engineering computing; rectifying circuits; thyristor convertors; diagnosis automation; neural network; power electronic circuits fault diagnosis; three-phase SCR rectifier circuit; training; waveform analysis; Automation; Circuit faults; Circuit simulation; Electrical fault detection; Fault detection; Fault diagnosis; Neural networks; Power electronics; Rectifiers; Thyristors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics and Drive Systems, 1999. PEDS '99. Proceedings of the IEEE 1999 International Conference on
  • Print_ISBN
    0-7803-5769-8
  • Type

    conf

  • DOI
    10.1109/PEDS.1999.794566
  • Filename
    794566