• DocumentCode
    2825770
  • Title

    Hybrid method for the diagnosis of electrical rotary machines by vibration signals

  • Author

    Sanz, Fredy A. ; Ramirez, Juan M. ; Correa, Rosa E.

  • Author_Institution
    Dept. of Electr. Eng., CINVESTAV - GDL, Zapopan, Mexico
  • fYear
    2010
  • fDate
    26-28 Sept. 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The vibration study in rotational electrical machines is a research topic that involves mathematical modeling, model identification, and signal analysis, among others. The failures in motors and generators modify the vibration signals. In this paper, the use of Adaptive Networks Based on Fuzzy Inference System (ANFIS) is proposed for rotary electrical machines´ diagnosis, because it is able to achieve consistent approximations of machines´ behavior when facing a faulty condition or functioning normally. Results using actual measurements are valuable and give higher expectations for the future.
  • Keywords
    electric generators; electric machines; electric motors; ANFIS; adaptive networks; electrical rotary machines diagnosis; fuzzy inference system; generators; mathematical modeling; model identification; motors; rotational electrical machines; signal analysis; vibration signals; Adaptive systems; Bars; Induction motors; Time frequency analysis; Vibration measurement; Vibrations; ANFIS; Electrical machines; Faults; Vibrations; Wavelet;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    North American Power Symposium (NAPS), 2010
  • Conference_Location
    Arlington, TX
  • Print_ISBN
    978-1-4244-8046-3
  • Type

    conf

  • DOI
    10.1109/NAPS.2010.5619959
  • Filename
    5619959