• DocumentCode
    2565686
  • Title

    An extraction computational algorithm based on the Morlet wavelet coefficient spectrum

  • Author

    Putra, T.E. ; Abdullah, S. ; Nuawi, M.Z.

  • Author_Institution
    Dept. of Mech. & Mater. Eng., Univ. Kebangsaan Malaysia, Bangi, Malaysia
  • fYear
    2009
  • fDate
    18-19 Nov. 2009
  • Firstpage
    68
  • Lastpage
    73
  • Abstract
    This paper discussed on the effectiveness of the Morlet wavelet to generate new edited signal. The 122.4 second SAESUS strain signal was edited based on the Morlet wavelet coefficient amplitude level. Segments with wavelet coefficient amplitude level lower than Cut Off Level (COL) were removed. Furthermore, extracted fatigue damaged segments were retained and then were joined in order to gain new edited signal. The signal statistical parameter and fatigue damaging values should be as accurate as possible for all signals. From the analysis, the 25,000 με was selected to be the optimum COL value since the level did not change the signal behaviour. This value gave a 14 % reduction in length with only 6.1 % reduction in the fatigue damage. This indicated that the Morlet wavelet can be successfully applied to compress the original signal without changing the main history as well.
  • Keywords
    fatigue; fatigue testing; signal processing; statistical analysis; wavelet transforms; Morlet wavelet coefficient spectrum; SAESUS strain signal; cut off level; edited signal; extraction computational algorithm; fatigue damaged segments; fatigue damaging values; signal statistical parameter; Capacitive sensors; Continuous wavelet transforms; Fatigue; Life estimation; Signal analysis; Signal processing; Testing; Time frequency analysis; Wavelet analysis; Wavelet coefficients;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Image Processing Applications (ICSIPA), 2009 IEEE International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-5560-7
  • Type

    conf

  • DOI
    10.1109/ICSIPA.2009.5478722
  • Filename
    5478722