• DocumentCode
    319481
  • Title

    Detection of rolling-element bearing signal corrupted by noise of similar frequency using adaptive noise cancellation

  • Author

    Tan, C.C. ; Okada, Y.

  • Author_Institution
    Queensland Univ. of Technol., Brisbane, Qld., Australia
  • Volume
    1
  • fYear
    1997
  • fDate
    9-12 Sep 1997
  • Firstpage
    108
  • Abstract
    The detection of a defective bearing signal corrupted by background machine noise and strong shaft unbalance is illustrated by using adaptive noise cancellation technique. A trial and error method is adopted to determine the optimum convergency factor for the adaptation process. Successful detection of the desired bearing signal depends on the choice of convergency factor and the location of the reference sensor for the measurement of correlated noise. Although the results show a strong potential for its application in detecting spall type bearing signal, a more definitive approach needs to be developed for determining the convergency factor for the adaptation process
  • Keywords
    acoustic noise; acoustic noise measurement; acoustic signal detection; adaptive signal processing; convergence of numerical methods; machine bearings; noise abatement; vibration measurement; adaptive noise cancellation; background machine noise; correlated noise measurement; defective bearing signal; noise corrupted signal; optimum convergency factor; reference sensor location; rolling-element bearing signal detection; spall type bearing signal; trial and error method; vibration signal; Acoustic signal detection; Adaptive filters; Adaptive signal detection; Background noise; Frequency; Noise cancellation; Noise generators; Shafts; Signal detection; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information, Communications and Signal Processing, 1997. ICICS., Proceedings of 1997 International Conference on
  • Print_ISBN
    0-7803-3676-3
  • Type

    conf

  • DOI
    10.1109/ICICS.1997.647067
  • Filename
    647067