Particle Swarm Optimization And Its Applied Research In The Structural Dynamic Modification

Recent years, the use of new structures and new materials has given rise to some structural dynamic problems because the rigidity of structures is reduced although it effectively improves the reduction of the structures' masses. Because of this, the structural model updating has become a multidisciplinary problem in the dynamics field. In this paper, a newly emerged efficient evolutionary computation technique -the Particle swarm optimization algorithm is investigated, including the principal theory, methods to realization and current application. Then the Particle Swarm optimization algorithm is applied to the structural model updating of a five-floor structure, from which the updated rigidity of the structure is obtained. The precision of model updating is measured by the similarities (ER and MAC) between experimentally measured mode data and the mode data computed by the updated model. In addition, the results computed by means of Particle swarm optimization algorithm are compared with the results computed by other methods such as Sensitivity analysis, neural network and Genetic algorithm etc. Conclusions can be drawn from the comparison that the Particle swarm optimization algorithm gives more appropriate results than those of other methods so updating structural model by PSO algorithm is valid.