• DocumentCode
    527409
  • Title

    Denoising method for cracks of hydraulic turbine blades based on independent component analysis

  • Author

    Wang, Xiang-hong ; Shao, Yi-min ; Hu, Hong-wei ; Fu, Jun-qin

  • Author_Institution
    Sch. of Automobile & Mech. Eng., Changsha Univ. of Sci. & Technol., Changsha, China
  • Volume
    3
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    1419
  • Lastpage
    1422
  • Abstract
    Cracks of hydraulic turbine unit are very dangerous to the safety of power station. The crack signals are usually contaminated by strong background noise. Thus extraction of the crack signals is studied in the paper. Independent component analysis (ICA) technique is used to extract the crack signal mixed with white Gaussian noise and operating background noise of the hydraulic turbine unit. It concludes that the method can separate the wanted signal. The denoising result is hardly affected by input signal-to-noise ratios (SNRs) and frequency ranges of signals. Furthermore, the extracted signal has small nuances with the real signal in wave shape. As a result, ICA technique is a better method to extract weak signals.
  • Keywords
    Gaussian noise; blades; hydraulic turbines; independent component analysis; signal denoising; white noise; background noise; crack signals; denoising method; hydraulic turbine blades; independent component analysis; power station safety; white Gaussian noise; Hydraulic turbines; Independent component analysis; Noise measurement; Noise reduction; Signal to noise ratio; Time frequency analysis; Denoising; Hydraulic turbine; ICA; crack;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5582575
  • Filename
    5582575