Structural damage identification using power spectral density and an evolutionary algorithm

Abstract

identification studies. An evolutionary algorithm is subsequently used to evolve the optimal model parameters introduced for different damage conditions. Given the complex search space, a covariance matrix adaptation evolution strategy algorithm provides a robust optimization tool in this domain. It is shown that this approach is capable of detecting structural damage in both noisy and noise-free environments.,This paper describes a new global damage identification framework for monitoring of civil structures. In order to localize and estimate the severity of damage regions, a one-stage model-based Bayesian probabilistic damage detection approach is proposed. This method,which is based on the response power spectral density of the structure, enjoys the advantage of broadband frequency information and can be implemented on input-output as well as output-only damage ,. © 2013 Taylor & Francis Group, London.