• DocumentCode
    1799213
  • Title

    Bearing defect diagnosis based on harmonic wavelet transform and singular value ratio spectrum

  • Author

    Hou Zhefei ; Wang YunPeng ; Kang Yong

  • Author_Institution
    Dalian Air Force Commun. NCO Acad., Dalian, China
  • fYear
    2014
  • fDate
    18-20 Aug. 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A novel signal processing algorithm was proposed here for vibration signal analysis in condition monitoring and health diagnosis of rolling bearings. Such technique required an envelope being extracted from vibration signal with Harmonic Wavelet Transform. The principal periodic component in the envelope was subsequently detected, enhanced and reconstructed with sweep frequency method based on singular value ratio (SVR) spectrum. Such signal processing approach was experimentally evaluated by using vibration signals measured on rolling element bearings that contained localized structural defects with proved validity and efficiency.
  • Keywords
    condition monitoring; rolling bearings; signal reconstruction; vibrational signal processing; vibrations; wavelet transforms; SVR spectrum; condition monitoring; envelope extraction; harmonic wavelet transform; health diagnosis; localized structural defects; principal periodic component detection; principal periodic component enhancement; principal periodic component reconstruction; rolling bearing defect diagnosis; rolling element bearings; signal processing algorithm; singular value ratio spectrum; sweep frequency method; vibration signal analysis; Harmonic analysis; Time-frequency analysis; Vibrations; Wavelet analysis; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Information Processing (ICICIP), 2014 Fifth International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-1-4799-3649-6
  • Type

    conf

  • DOI
    10.1109/ICICIP.2014.7010334
  • Filename
    7010334