• DocumentCode
    3154590
  • Title

    Condition recognition of induction machine under various loads

  • Author

    Wu, Rong-Ching ; Tsao, Ta-Peng

  • Author_Institution
    Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan
  • Volume
    2
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    603
  • Abstract
    This paper offers a complete method to deal with the condition recognition for induction machines under different loads. In actual operation, the loads of induction machines vary within a certain range. When the signal is transformed into spectrum, the load variation causes band drifts and amplitude variation. The load factor influences the result of recognition seriously. This paper offers band adjustment and feature extraction to solve the recognition problems caused by loads and faults. Employing band adjustment, the method eliminates the phenomenon of band drift under different operation condition. Employing feature extraction, the method decreases the sensitivity of features to loads. Then, load influences on condition recognition for an induction machine will descend to a minimum. The method afforded in this paper is verified by experiment, and proves its feasibility with high accuracy
  • Keywords
    asynchronous machines; electrical faults; feature extraction; signal processing; amplitude variation; band drifts; condition recognition; feature extraction; induction machine; load factor; load variation; Feature extraction; Frequency; Induction machines; Load management; Narrowband; Sampling methods; Signal analysis; Signal detection; Time factors; Vibration measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics and Drive Systems, 1999. PEDS '99. Proceedings of the IEEE 1999 International Conference on
  • Print_ISBN
    0-7803-5769-8
  • Type

    conf

  • DOI
    10.1109/PEDS.1999.792671
  • Filename
    792671