Bayesian damage characterization based on probabilistic model of scattering coefficients and hybrid wave finite element model scheme

Abstract

Ultrasonic Guided Wave(GW) has been proven to be sensitive to small damage. Motivated by the fact that the quantitative relationship between wave scattering and damage intensity can be described by scattering properties, this study aims at proposing a new probabilistic damage characterization method based on the scattering coefficients in tandem with hybrid wave finite element model (WFEM) scheme. The probabilistic distribution properties of the scattering coefficients estimated using measured ultrasonic guided waves in the frequency domain are inferred based on absolute complex ratio statistics. The theoretical scattering coefficients can be efficiently calculated using WFEM which combines conventional finite element analysis with periodic structure theory. Based on the probabilistic distribution of reflection/transmission coefficients, the likelihood function connecting the theoretical model responses containing the parameters to be updated and the measured responses are formulated within a unified Bayesian system identification framework to account for various uncertainties. The transitional Monte Carlo Markov Chain (TMCMC) is used to sample the posterior probability density function of the updated parameters. A numerical example is utilized to verify the accuracy of the proposed algorithm. Results indicate that the strategies proposed in this study can quantify the uncertainties of damage characterization © 2019 The authors.