An ED-PSO model updating algorithm for structure health monitoring of beam-like structures

Abstract

Cracks and other damages generated during the service of bridges can reduce the load bearing capacity and threaten operational safety.Finite Element Model Updating (FEMU), as one of the important means of structural health diagnosis, identifies structural damage through changes in model parameters. The three key factors of FEMU are updating variables, objective functions, and optimization algorithms. The poor selection of the above three factors in existing research leads to high calculation errors in model updating, and inevitably lead to the inability of the finite element model to carry out structural health monitoring, affecting the normal operation of the structure. In order to solve the above problems, this paper combines previous research and establishes a model updating algorithm based on the combination of eigenvector difference approach and particle swarm optimization (ED-PSO). The validity and accuracy of this method are verified by finite element analysis of a simply supported beam. Compared with the existing model updating algorithms based on the combination of static and dynamic methods and particle swarm optimization (CSD-PSO), the results show that the proposed ED-PSO model updating algorithm has higher accuracy and is expected to be better applied to bridge finite element model updating research.