• DocumentCode
    483148
  • Title

    A new approach to identify inrush current based on generalized S-transform

  • Author

    Jiao, Shangbin ; Wang, Sha ; Zheng, Gang

  • Author_Institution
    Xi´´an Univ. of Technol., Xi´´an
  • fYear
    2008
  • fDate
    17-20 Oct. 2008
  • Firstpage
    4317
  • Lastpage
    4322
  • Abstract
    A novel approach to identify inrush current and internal fault current for power transformer protection based on generalized S-transform is presented. Generalized S-transform is a very powerful tool for non-stationary signal analysis giving the information of transient currents both in time and in frequency domains. It is used to extract patterns from inrush current and internal faults. The time-frequency contours are obtained after generalized S-transform, it is found that the time-frequency contours in case of inrush current are different from that in case of internal faults. The spectral energy and standard deviation from the generalized S-transform of signal are computed, classification of inrush current and internal faults is done by BP neural networks. Simulation results and dynamic test results indicate that this technique is effective under different fault conditions.
  • Keywords
    Fourier transforms; backpropagation; fault currents; neural nets; power engineering computing; power transformer protection; time-frequency analysis; transients; wavelet transforms; BP neural network; fault current; frequency-domain analysis; generalized S-transform; inrush current identification; nonstationary signal analysis; power transformer protection; short time Fourier transform; standard deviation; time-domain analysis; transient current; wavelet transform; Computer networks; Data mining; Fault currents; Fault diagnosis; Frequency domain analysis; Power transformers; Signal analysis; Surge protection; Time frequency analysis; Transient analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Machines and Systems, 2008. ICEMS 2008. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-3826-6
  • Electronic_ISBN
    978-7-5062-9221-4
  • Type

    conf

  • Filename
    4771552