• DocumentCode
    776318
  • Title

    Toward automatic classification of partial discharge sources with neural networks

  • Author

    Hirata, Akimasa ; Nakata, Syou ; Kawasaki, Zen-Ichiro

  • Author_Institution
    Nagoya Inst. of Technol., Japan
  • Volume
    21
  • Issue
    1
  • fYear
    2006
  • Firstpage
    526
  • Lastpage
    527
  • Abstract
    In this letter, we propose an automatic classification scheme of discharge sources on the basis of Fourier spectrum for received electromagnetic (EM) pulses. Confirming the reproducibility of EM pulses from each source validates this scheme. The recognition rate for six discharge sources is 80% or better. The feature of our system is time efficient and to treat hundreds of pulses.
  • Keywords
    Fourier analysis; neural nets; partial discharge measurement; power apparatus; power engineering computing; signal classification; Fourier spectrum; neural networks; partial discharge sources automatic classification; received electromagnetic pulses; Dielectrics and electrical insulation; Fault location; Multiple signal classification; Neural networks; Partial discharges; Power system reliability; Pulse power systems; Remote sensing; Reproducibility of results; Sensor arrays; Digital systems; fault diagnosis; neural-network applications; partial discharges;
  • fLanguage
    English
  • Journal_Title
    Power Delivery, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8977
  • Type

    jour

  • DOI
    10.1109/TPWRD.2005.848439
  • Filename
    1564248