LAUSR

Abstract A new pattern recognition based structural damage detection method using structural mode-shapes along with natural frequencies is presented in this article. A three span RC bridge is selected to verify the proposed method. To conquer the complexities of finite element simulation of the real structure, SAP2000 is employed for FE modeling and analyzing the structure and thus generating the input parameters for damage assessment process. Having the modal data for the intact and damaged structure, extraction of damage properties becomes a “pattern recognition” or “feature discrimination” problem, while Twin Gaussian Process (TGP) as an advantageous pattern recognition technique is employed to compare the measured mode-shapes and frequencies with their healthy state values and identify the damaged elements. The results of this study shows that the suggested method performs precisely in damage identification of structures having an updated as-built model. Furthermore, it can be concluded that TGP, which is used for damage detection process in this study, is an efficient tool to detect both location and severity of structural damages in single and multiple damage scenarios. The proposed method can be widely used for model updating and damage detection of real structures without any restrictions in modeling.