• DocumentCode
    1768075
  • Title

    Broken rotor bars detection via Park´s vector approach based on ANFIS

  • Author

    Zarei, Jafar ; Hassani, H. R. ; Wei, Zhihui ; Karimi, Hamid Reza

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Shiraz Univ. of Technol., Shiraz, Iran
  • fYear
    2014
  • fDate
    1-4 June 2014
  • Firstpage
    2422
  • Lastpage
    2426
  • Abstract
    Many attempts have been made on fault diagnosis of induction motors based on frequency and time domain analysis of stator current. In this paper, first the Park´s vector transformation and frequency analysis for fault detection of induction motors are introduced. Then a smart approach using Adaptive Neuro Fuzzy Inference System (ANFIS) is proposed. This approach uses the time domain features derived from the Park´s vector transformation of stator current. By the proposed method, a partial break including 5 mm crack on a bar, one broken bar and two broken bars using experimental data are investigated. It will be shown that features derived from Park´s vector compared to features obtained from a phase current, have better results.
  • Keywords
    fault diagnosis; frequency-domain analysis; fuzzy reasoning; induction motors; rotors; stators; time-domain analysis; ANFIS; Park vector transformation; adaptive neuro fuzzy inference system; broken rotor bars detection; fault detection; fault diagnosis; frequency analysis; frequency domain analysis; induction motors; size 5 mm; stator current; time domain analysis; Bars; Fault detection; Induction motors; Rotors; Stator windings; Vectors; ANFIS; Park´s transformation; broken rotor bars; fault diagnosis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics (ISIE), 2014 IEEE 23rd International Symposium on
  • Conference_Location
    Istanbul
  • Type

    conf

  • DOI
    10.1109/ISIE.2014.6864999
  • Filename
    6864999