Non-Iterative Eigenstructure Assignment-Based Finite Element Model Updating for Probabilistic Identification of Bridge Damage

Finite element model (FEM) updating is widely used in damage identification for its clear physical meaning and standardized process. However, the traditional FEM is updated by an iterative algorithm, which suffers from low-computational efficiency. There are too many parameters that need to be updated and hence it is difficult to converge during optimization. Besides, the FEM and the information used for updating are uncertain for real bridges, which seriously affect the effectiveness of damage identification. This paper proposes a probabilistic identification method for structural damage by using the non-iterative eigenstructure assignment (ESA)-based FEM updating. First, a non-iterative ESA-based FEM updating approach is proposed by using the frequency and mode shape. Second, the damage location is determined by comparing the global stiffness matrix of the FEM before and after updating. Third, the elemental damage severity is estimated according to the functional relationship between the principal diagonal element variation in the global stiffness matrix and the elemental damage severity. Then, a probabilistic damage identification method is presented considering the uncertainty effects by combining Monte Carlo and non-iterative ESA- based FEM updating. Finally, the effectiveness and superiority of the proposed damage identification method are verified by numerical and experimental examples. The results indicate that the non-iterative technique substantially improves the efficiency of FEM updating and damage identification of bridges considering its uncertainty.