%0 Journal Article
%T Damage detection in structures using finite element model updating based on changes in wavelet transform coefficients of a correlation function
%J Amirkabir Journal of Civil Engineering
%I Amirkabir University of Technology
%Z 2588-297X
%A sadeghian, Mohsen
%A Esfandiari, Akbar
%A Fadavie, Manouchehr
%D 2023
%\ 05/22/2023
%V 55
%N 3
%P 665-680
%! Damage detection in structures using finite element model updating based on changes in wavelet transform coefficients of a correlation function
%K damage detection
%K Finite element model updating
%K Auto Correlation
%K Wavelet transform
%K Sensitivity analysis
%R 10.22060/ceej.2023.20796.7528
%X In this paper, an innovative finite element updating method is presented based on the sensitivity of wavelet transform coefficients of correlations function structural parameters is proposed to identify the damage. The Quasi-linear sensitivity of the wavelet coefficients of the WTCF concerning the structural parameters is evaluated based on incomplete measured structural responses. This WTCF sensitivity is more sensitive to local structural changes than the wavelet transform function response sensitivity. The model is updated by the wavelet transform coefficients achieved in the frequency range in the vicinity of the resonances, in which damping and incomplete measurements have no significant effect on the results of the parameter estimation. The proposed algorithm is used to estimate the structural parameters of the frame model. By the solution of the sensitivity equation through the Least-squares method, the finite element model of the structure is updated for estimation of the location and severity of structural damages, simultaneously. The proposed method was successfully applied to a 2D frame model using simulated data contaminated by measurement and modeling errors. The robustness of the method against modeling and mass measurement errors is investigated by adding random errors to the mass parameters of the frame model.
%U https://ceej.aut.ac.ir/article_5075_015308d69dec22fdb949b18f7bc7e104.pdf