Transfer function‐based Bayesian damage detection under seismic excitation

Summary Transfer function (TF) data are recognized as diagnostic features in damage detection procedure. The objective of this paper is to present a damage detection method in Bayesian paradigm based on TF data due to ground excitation. The measured seismic responses of the structure in the frequency domain are adopted to obtain displacement TFs and the structural natural frequencies are identified from observed TFs. The derived features are utilized for Bayesian structural damage detection. In addition, the challenging issue of underlying flexible soil in real cases has been addressed. The proposed technique is applied to a numerical shear frame to evaluate the capability of the method. An experimental study on a six‐story steel building has been validated to demonstrate the capability of the method for damage detection purpose. The results of studied cases indicated that the proposed method is capable of identifying the location and the severity of damage precisely.