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Wavelet coefficients based on spatial wavelets are used as damage indicators to identify the damage location as well as the size of the damage in a laminated composite beam with localized matrix cracks. A finite element model of the composite beam is used in conjunction with a matrix crack based damage model to simulate the damaged composite beam structure. The modes of vibration of the beam are analyzed using the wavelet transform in order to identify the location and the extent of the damage by sensing the local perturbations at the damage locations. The location of the damage is identified by a sudden change in spatial distribution of wavelet coefficients. Monte Carlo Simulations (MCS) are used to investigate the effect of ply level uncertainty in composite material properties such as ply longitudinal stiffness, transverse stiffness, shear modulus and Poisson's ratio on damage detection parameter, wavelet coefficient. In this study, numerical simulations are done for single and multiple damage cases. It is observed that spatial wavelets can be used as a reliable damage detection tool for composite beams with localized matrix cracks which can result from low velocity impact damage. [ABSTRACT FROM AUTHOR]

This paper presents a technique for structure damage detection based on spatial wavelet analysis. The innovation of the proposed paper is that both the positions and depths of multi-cracks can be estimated from spatial wavelet based method. First, the mode shapes of free vibration and natural frequencies of the multiple cracked beams are obtained. The crack type is open crack and is represented as a rotational spring. Then the mode shapes are analysed by wavelet transformation to get the positions of the cracks. When the positions of the cracks have been known from the plot of wavelet coefficients, the natural frequencies can be used to predict the depth of the cracks through the characteristic equation. If the number of cracks is n, the first n natural frequencies are used to predict the depth of the cracks. It is observed that the positions and depths of the cracks can be predicted with acceptable precision even though there are many cracks in the beam. [Copyright &y& Elsevier]

This paper presents a technique for blade damage detection based on spatial wavelet analysis. The wavelet transform is used to analyze spatially distributed signals (e.g. mode shape) of cracked thick rotating blades. First, a finite element model is applied to the vibration of a thick rotating blade with a single edge crack. The effects of transverse shear deformation and rotatory inertia are taken into account. Then the mode shapes of the cracked rotating blade are analyzed by wavelet transformation. The effects of crack locations and sizes on the wavelet coefficients are studied. It is found that the distributions of the wavelet coefficients can identify the crack position of the rotating blades by showing a peak at the position of the crack. Then the signals are analyzed by wavelet transform. It is found that the distributions of the wavelet coefficients can identify the crack position. Assumed measurement errors are added to nth mode shape for evaluating the effect of measurement errors on the capability of detecting crack position. The moving average method is used to process the data with assumed measurement errors. The crack positions can also be identified when there exist assumed measurement errors. [Copyright &y& Elsevier]

This paper presents a technique for structure damage detection based on spatial wavelet analysis. Many damage detection methods require modal properties before and after damage. This method only needs the spatially distributed signals (e.g. the displacements or mode shapes) of the rectangular plate after damage. First, spatially distributed signals of the rectangular plate with damage are obtained by finite element method. The damaged region is represented as the elements with reduced stiffness. Then these spatially distributed signals are analyzed by wavelet transformation. It is observed that distributions of the wavelet coefficients can identify the damage position of rectangular plate by showing a peak at the position of the damage. It is also demonstrated that this method is very sensitivity to the damage size. [Copyright &y& Elsevier]

This paper presents a technique for structure damage detection based on spatial wavelet analysis. The wavelet transform is used to analyze the mode shape of a Timoshenko beam. First, the mode shapes of the Timoshenko beam containing a transverse crack are obtained. The crack is represented as a rotational spring. Then these spatially distributed signals are analyzed by wavelet transformation. It is observed that distributions of the wavelet coefficients can identify the crack position of Timoshenko beam by showing a peak at the position of the crack. It is also demonstrated that the crack position can be detected by this method even though the crack is very small. Assumed measurement errors are added to the mode shape for evaluating the effect of measurement errors on the capability of detecting crack position. The moving average method is used to process the data with assumed measurement errors. The crack positions can also be identified when there exist assumed measurement errors. [Copyright &y& Elsevier]