• DocumentCode
    1714967
  • Title

    Application of NN as a scheme of off-line PD diagnosis method on traction motor stator coil

  • Author

    Jang, Dong-Uk ; Seong-hee Park ; Lim, Kee-Joe ; Kang, Seong-Hwa ; Park, Hyun-June

  • Author_Institution
    Korea Railroad Res. Inst., South Korea
  • Volume
    3
  • fYear
    2005
  • Firstpage
    744
  • Abstract
    Insulation failure of traction motor stator coil depends on the continuous stress imposed on it and knowing the insulation condition is important for safe operation. In this paper, application of NN (neural network) as a scheme of off-line PD (partial discharge) diagnosis method, which occurs at the stator coil of traction motor, was studied. For PD data acquisition, three defective models are made; internal void discharge model, slot discharge model and surface discharge model. PD data for recognition were acquired from PD detector. Statistical distributions and parameters are calculated to distinguish between model discharge sources. Also these statistical distribution parameters are applied to classify PD sources by NN, with a good recognition rate on the discharge sources.
  • Keywords
    coils; failure analysis; insulation testing; machine insulation; neural nets; partial discharge measurement; power engineering computing; statistical distributions; stators; surface discharges; traction motors; data acquisition; insulation failure; internal void discharge model; neural network; offline PD diagnosis method; partial discharge; slot discharge model; statistical distributions; surface discharge model; traction motor stator coil; Coils; Data acquisition; Fault location; Insulation; Neural networks; Partial discharges; Statistical distributions; Stators; Stress; Traction motors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Insulating Materials, 2005. (ISEIM 2005). Proceedings of 2005 International Symposium on
  • Print_ISBN
    4-88686-063-X
  • Type

    conf

  • DOI
    10.1109/ISEIM.2005.193478
  • Filename
    1496282