• DocumentCode
    497344
  • Title

    Gear Fault Diagnosis Based on EMD and AR Spectrum Analysis

  • Author

    Ai, Shufeng ; Li, Hui ; Fu, Lihui

  • Author_Institution
    Dept. of Commun. Technol., Zhejiang Univ. of Media & Commun., Hangzhou, China
  • Volume
    1
  • fYear
    2009
  • fDate
    11-12 April 2009
  • Firstpage
    673
  • Lastpage
    676
  • Abstract
    A novel method to fault diagnosis of gear crack based on empirical mode decomposition (EMD) and autoregressive (AR) spectrum is presented. This method can carry out empirical mode decomposition and extract feature information of different machine parts in condition monitoring and fault diagnosis of machinery. The main objective of empirical mode decomposition is to separate the time series data into components with different time scale. Then the AR model estimation is applied to each intrinsic mode function and the AR spectrum is obtained. As an example, the vibration signal of a gearbox is analyzed. The experimental results show that this method based on empirical mode decomposition and autoregressive spectrum can effectively diagnose the crack faults of gear.
  • Keywords
    autoregressive processes; condition monitoring; fault diagnosis; feature extraction; gears; spectral analysis; time series; vibrations; AR spectrum analysis; autoregressive spectrum; condition monitoring; empirical mode decomposition analysis; fault diagnosis; feature extraction; gears; machine parts; time series data; vibration signal; Cepstral analysis; Data analysis; Fault detection; Fault diagnosis; Fourier transforms; Gears; Machinery; Signal analysis; Time frequency analysis; Wavelet analysis; AR Spectrum; Vibration; empirical mode decomposition; fault diagnosis; gear;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
  • Conference_Location
    Zhangjiajie, Hunan
  • Print_ISBN
    978-0-7695-3583-8
  • Type

    conf

  • DOI
    10.1109/ICMTMA.2009.430
  • Filename
    5203062