• DocumentCode
    2530920
  • Title

    Application of wavelet transform and MLP neural network for Ferroresonance identification

  • Author

    Mokryani, G. ; Haghifam, M.-R.

  • Author_Institution
    Islamic Azad Univ., Ilkhchi
  • fYear
    2008
  • fDate
    20-24 July 2008
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper an efficient method for detection of ferroresonance in distribution transformer based on wavelet transform is presented. Using this method ferroresonance can be discriminate from other transients such as capacitor switching, load switching, transformer switching. Wavelet transform is used for decomposition of signals and Multi Layer Perceptron (MLP) neural network used for classification. Ferroresonance data and other transients are obtained by simulation using EMTP program. Results show that the proposed procedure is efficient in identifying ferroresonance from other transients.
  • Keywords
    ferroresonant circuits; multilayer perceptrons; neural nets; power engineering computing; power transformers; wavelet transforms; EMTP program; MLP neural network; capacitor switching; distribution transformer; ferroresonance identification; load switching; multilayer perceptron neural network; transformer switching; wavelet transform; Capacitance; Capacitors; Ferroresonance; Frequency; Hidden Markov models; Inductance; Multiresolution analysis; Neural networks; Voltage control; Wavelet transforms; EMTP program; Ferroresonance; MLP neural network; Wavelet transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE
  • Conference_Location
    Pittsburgh, PA
  • ISSN
    1932-5517
  • Print_ISBN
    978-1-4244-1905-0
  • Electronic_ISBN
    1932-5517
  • Type

    conf

  • DOI
    10.1109/PES.2008.4596061
  • Filename
    4596061