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Novel Reduced Model Based Damage Detection of Frame Structures

D. ZHANG, H. LI

Abstract


Due to the complexity of frame structures, a simple shear model is frequently adopted for the frame to model its dynamic responses when performing structural damage detection. The estimated story stiffnesses of the shear model are used to infer the damage status of the frame. However, as pointed out in many studies, due to the existence of modeling error, using a shear model to carry out damage detection for the frame often leads inaccurate damage detection results. In this paper, a novel reduced model is proposed for the damage detection of frame structures, which, compared with shear model, can significantly reduce the modeling error and, thus, improve damage detection accuracy for the frame structure. Moreover, an iterative substructure identification method is proposed to identify the parameters of the reduced model. Finally, a numerical example of an eight-story frame structure is utilized to demonstrate the effectiveness of the proposed damage detection method; the results show that, by using the reduced model, the damage detection accuracy of the frame structure is greatly improved, compared with using a shear structure model.

doi: 10.12783/SHM2015/169


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