Application of Bayesian statistical method in sensitivity-based seismic damage identification of structures: Numerical and experimental validation

Abstract

Most of the developed sensitivity-based damage detection methods are based on the application of external excitations which could be prohibitive due to infeasible excitation of all structural degrees of freedom. In this regard, identification of damage properties using seismic structural response would be advantageous. In this research, sensitivity-based finite element model updating method is proposed to identify structural damage by earthquake response in the frequency domain and the transfer function of the structure due to ground excitation. The obtained sensitivity equation is solved by linear least square method through defining constraints on the design variables. Since the attainable measured data are restricted by limits on the instrumentations and preciseness of the measurements and due to the fact that only a few of the lower modes of a structure can generally be determined with confidence, a Bayesian statistical method is utilized to enhance the reliability of the predicted damage properties. The proposed technique is applied to a numerical frame model and an experimental six-story steel structure with various scenarios of story stiffness reduction. The results are indicative of the capability of the proposed method for identification of damage location and severity.

Damage identification of structures based on sensitivity equations using PCA and PSD data

“…The proposed approach was employed for the 2D structures for a steel truss 7 and a steel frame 35 to demonstrate the ability and efficiency of the presented sensitivity equation to identify structural damage. To define the accuracy of the measurements, the natural frequencies of the structures have been checked against the references.…”

“…To define the accuracy of the measurements, the natural frequencies of the structures have been checked against the references. 7,35…”

“…To define the accuracy of the measurements, the natural frequencies of the structures have been checked against the references. 7,35 The PSD data were simulated numerically using the FEMs of the two structures. In real tests, it is not possible to avoid error; thus, this was dealt with by producing slight deviance in the experimental dynamic properties.…”

Efficient two-step procedure for parameter identification and uncertainty assessment in model updating problems

“…Its robustness in dealing with uncertainties is widely explored and it shows its applicability and feasibility for structural health monitoring (Nguyen et al, 2019;Ponsi et al, 2022). However, Bayesian model updating needs to solve multidimensional integration problems and it requires the solution of a nonlinear optimization problem (Ching and Beck, 2004;Vahedi et al, 2018). This often requires considerable computational time and could be unusable in real-time or near-realtime damage detection.…”