• Title of article

    Structural damage detection and calibration using a wavelet–kurtosis technique

  • Author/Authors

    Pakrashi، نويسنده , , V. and Basu، نويسنده , , B. and O’ Connor، نويسنده , , A.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2007
  • Pages
    12
  • From page
    2097
  • To page
    2108
  • Abstract
    Some key factors in the field of damage detection of structures are the efficient and consistent detection of the presence, location and the extent of damage. A detailed numerical study has been performed in this paper addressing these issues for a beam element with an open crack. The first natural modeshape of the beam with an open crack has been simulated using smeared, lumped and continuous crack models involving various degrees of complexity. The static deflected shape of the same beam has also been simulated under vertical static loading. Gaussian white noise of different intensities has been synthetically introduced to both the simulated damaged modeshape and the static deflected shape. Wavelet analysis has been performed on the simulated modeshape and the static deflected shape for locating the damage. A new wavelet–kurtosis based calibration of the extent of damage has been performed for different crack depth ratios and crack positions including the effects of varying signal to noise ratio. An experimental validation of this method has been carried out on a damaged aluminium beam with open cracks of different extent. The damaged shape has been estimated by using a novel video camera based pattern recognition technique. The study in this paper shows that wavelet analysis in conjunction with a kurtosis based damage calibration can be useful in the identification of damage to structures and is applicable under the presence of measurement noise.
  • Keywords
    signal to noise ratio , kurtosis , wavelets , Open crack , Windowing , Masking
  • Journal title
    Engineering Structures
  • Serial Year
    2007
  • Journal title
    Engineering Structures
  • Record number

    1641446