• DocumentCode
    3660255
  • Title

    Gearbox Fault Detection and Diagnosis Based on EEMD De-noising and Power Spectrum*

  • Author

    Tao Wang;Xing Wu;Tao Liu;Zheng-ming Xiao

  • Author_Institution
    Mechanical and electrical engineering college, Kunming University of Science and Technology, Yunnan province, China
  • fYear
    2015
  • Firstpage
    1528
  • Lastpage
    1531
  • Abstract
    The vibration signal of fault gear is related to non-stationary property, and the gear fault diagnosis will be seriously interfered by bearing signal and other noise signal. EEMD can adaptive decomposition of the vibration signal into different frequency components, but the precise extraction of useful signal is still a question. In this paper, a double determination criterion is presented to the EEMD method to reduce noise, and combined with the power spectrum of time-frequency analysis to diagnosis the fault of gearbox. The experimental results show that EEMD combined with Power spectrum can effectively extract the characteristic frequency from strong noise signals and diagnose the fault of gear.
  • Keywords
    "Gears","Time-frequency analysis","Fault diagnosis","Vibrations","Shafts","Noise"
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation, 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/ICInfA.2015.7279528
  • Filename
    7279528