• DocumentCode
    2451121
  • Title

    Angle Domain Average and Autoregressive Spectrum Analysis Based Gear Faults Diagnosis

  • Author

    Ai, Shufeng ; Li, Hui ; Fu, Lihui

  • Author_Institution
    Dept. of Commun. Technol., Zhejiang Univ. of Media & Commun., Hangzhou, China
  • fYear
    2009
  • fDate
    25-26 April 2009
  • Firstpage
    659
  • Lastpage
    662
  • Abstract
    In order to process the non-stationary vibration signals during run-up of gearbox, the method based on angle domain average and autoregressive spectrum analysis is presented. This new method combines angle domain average with angle domain average technique. Firstly, the vibration signal is sampled at constant time increments and then uses software to resample the data at constant angle increments.Secondly, the angle domain signal is preprocessed using angle domain average technique in order to eliminate the unrelated noise. In the end, the averaged signals are processed by autoregressive spectrum analysis. The experimental results show that the proposed method can effectively detect the gear crack faults.
  • Keywords
    autoregressive processes; condition monitoring; fault diagnosis; gears; signal processing; spectral analysis; vibrations; angle domain average analysis; angle domain signal; autoregressive spectrum analysis; gear crack faults; gear faults diagnosis; gearbox fault diagnosis; non-stationary vibration signals; Condition monitoring; Fault diagnosis; Frequency; Gears; Machinery; Sampling methods; Shafts; Signal analysis; Signal processing; Signal sampling; angle domain average; autoregressive spectrum; fault diagnosis; gear; vibration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence, 2009. JCAI '09. International Joint Conference on
  • Conference_Location
    Hainan Island
  • Print_ISBN
    978-0-7695-3615-6
  • Type

    conf

  • DOI
    10.1109/JCAI.2009.10
  • Filename
    5159089