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Wavelet Transform of Modal Data of Beam in Damage Detection Exercise
Most of the classical methods in damage detection technologies are based on natural frequency, mode shapes, curvature, strain energy etc. In recent years wavelet based damage detection has acquired considerable space in the related literature. The purpose of this study is to develop the wavelet coefficients based damage detection. The damage here is simulated as transverse cuts in the cantilever model. Finite element modal analysis is carried out to extract ten bending modes by Block Lanczos extraction algorithm. The modal data obtained is decomposed by Discrete Wavelet Transform into approximate coefficients and detail coefficients. The higher order curve obtained as detail coefficients contains much information about damage. The details are studied across many other wavelets types. The study focused to explore the effectiveness of different mother wavelets. The findings of the study are useful to select the suitable mother wavelet based on discrete wavelet transform. Higher modes have shown better sensitivity towards small level of damage. This established the necessity of higher order modes in damage detection methodologies. The work has benefitted in deciding the preferred wavelets in such damage detection problems. The results of various damage configurations fall in the same line pointing towards single mother wavelet selection, thus reconfirming the benefits of the method.
Damage Detection, Mode Shape, Signal Processing, Wavelet Transform.
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