Damage identification in steel plate structures considering bending and torsion moments using estimated seismic responses

Abstract

This paper proposes a model-free damage identification method and suggests an effective index for damage diagnosis in steel plate-like structures considering both the torsion and bending moments using only acceleration data, with no need for geometric characteristics. The basis for damage detection is the difference between healthy and damaged structural responses to different ground accelerations. In doing so, two Peak Ground Acceleration (PGA) scales, 0.05 (g), and 0.5 (g), labeled for the Loma Prieta ground motion, are considered. Four-node meshes are applied to reflect the torsion moments in the steel plate behavior. A multi-objective function, Fisher Information Matrix, is utilized, and four sensor locations are optimized to identify the locations most sensitive to damage. AutoRegressive Moving Average with exogenous input (ARMAX) system identification method is employed to obtain the structural displacement from the acceleration data and, subsequently, the displacement state equations of the nodes. With the aid of the structural displacement and its derivatives obtained through the central finite difference approximation method, damage to the plate structure is detected at PGA = 0.05 (g) and PGA = 0.50 (g) considering thickness changes based on the peak values manifested in the proposed damage detection index. Furthermore, the recorded structural acceleration responses at the desired scales of PGAs are fed into the 2D wavelet transform to detect damage imposed on the plate structure using the diagonal component of the wavelet transform. The results confirm that the proposed nonmodel-based approach successfully detects the single and multiple damage scenarios and can be used for a quick and judicious assessment of the steel plate behavior immediately after damage.