Research on probabilistic diagnosis-based structural damage identification using two-phase fusion of multi-source information

Abstract

Several de-noising techniques have been proposed previously. However, in structural damage identification, it is still difficult to effectively eliminate the influence of noise by using any de-noising technique due to the complexity of environmental noise. This difficulty leads to the failure of some damage identification indices when used in practical applications, despite their high sensitivity to damage in simulation analyses. This paper proposes a probabilistic diagnosis-based method involving the fusion of two-phase multi-source information. First, local decision results of structural damage were obtained by using the improved element damage variable and the element stiffness reduction factor. Then, the Dempster-Shafer(D-S) evidence theory was used to fuse the local decision results to obtain the final decision results. By performing a simulation analysis and dynamic tests of a reinforced concrete beam and steel beam, it was confirmed that the proposed procedure demonstrated good stability and noise resistance.