A Kriging Model Based Finite Element Model Updating Method for Damage Detection

Model updating is an effective means of damage identification and surrogate modeling has attracted considerable attention for saving computational cost in finite element (FE) model updating, especially for large-scale structures. In this context, a surrogate model of frequency is normally constructed for damage identification, while the frequency response function (FRF) is rarely used as it usually changes dramatically with updating parameters. This paper presents a new surrogate model based model updating method taking advantage of the measured FRFs. The Frequency Domain Assurance Criterion (FDAC) is used to build the objective function, whose nonlinear response surface is constructed by the Kriging model. Then, the efficient global optimization (EGO) algorithm is introduced to get the model updating results. The proposed method has good accuracy and robustness, which have been verified by a numerical simulation of a cantilever and experimental test data of a laboratory three-story structure.