A wavelet-based Bayesian damage identification technique using an evolutionary algorithm

Abstract

Structural damage identification is a challenging task, especially when response measurements have local discontinuities and display non-stationarity. This paper presents a one-stage model-based damage identification technique using wavelet power spectra to address this problem. To detect, locate and estimate the severity of damage, the finite element model is updated using a Bayesian probabilistic approach and a covariance matrix adaptation evolution strategy, taking into account the uncertainty caused by measurement noise and modelling error. A range of numerical simulations are used to evaluate the efficacy of the model under different damage scenarios, including: both single and multiple..