• DocumentCode
    405105
  • Title

    Negative sequence admittance average based detection of stator winding inter-turn short circuit fault in induction motors

  • Author

    XU, Boqiang ; Li, Heming ; Sun, Liling

  • Author_Institution
    North China Electr. Power Univ., Baoding, China
  • Volume
    2
  • fYear
    2003
  • fDate
    9-11 Nov. 2003
  • Firstpage
    867
  • Abstract
    Stator winding inter-turn short circuit fault (SWITSCF) occurs with a comparatively higher probability in induction motors. Based on both numerical simulation and experimental investigation, this paper points out that negative sequence admittance average can be viewed as the feature criterion and utilized to detect the fault. Moreover, this paper determines the relationship between negative sequence admittance average and operating condition of induction motors by utilizing BP neural network technique, as allows to setup appropriate detection threshold. Thus, negative sequence admittance average based detection method of SWITSCF in induction motors is presented in this paper.
  • Keywords
    backpropagation; electric admittance; fault diagnosis; induction motors; neural nets; numerical analysis; short-circuit currents; stators; BP neural network technique; induction motors; inter-turn short circuit fault detection; negative sequence admittance; numerical simulation; stator winding; Admittance; Circuit faults; Electrical fault detection; Fault detection; Induction motors; Neural networks; Numerical simulation; Rotors; Stator windings; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Machines and Systems, 2003. ICEMS 2003. Sixth International Conference on
  • Conference_Location
    Beijing, China
  • Print_ISBN
    7-5062-6210-X
  • Type

    conf

  • Filename
    1274187