Dynamic Structural Model Based On Particle Swarm Optimization Algorithm Is Modified

As the advancement of society and the development of civil engineering technology, more and more complicated bridges are applied to engineering. How to control and forecast the health of these complicated structure will be much important in project. It is an effective approach to detect the bridge's health by using the dynamical structural model updating method to identify the structure's damnification. In this dissertation, the development of dynamical structural model updating and the application of various algorithms in this updating have been introduced first, and analysed each algorithm's excellence or shortcoming, and the predominance of the particle swarm optimization applied in structural model updating. Then the algorithm is applied to dynamical structural model updating, this approach's creation ,development and its application in engineer also have been introduced in detail. In this dissertation ,the primary work is that we exercised the particle swarm optimization algorithm into updating the structure model, and across updating the model of cable bridge which named hu men bridge , we gaind different results in different complexion. We used the particle swarm optimization algorithm updated structural model in four dimensionality and six dimensionality, and than we used the mend particle swarm optimization algorithm updated structural in six dimensionality. By comparing the results before and after being updated , after being updated with the meterage data of reality, the amendment effect is satisfied with the result, which is accorded with the structure's natural vibration frequency and vibration mode(ER and MAC). So it is considerable to applied that the particle swarm optimization algorithm is able to complicated structure's dynamical model updating. Compared the updating effects of the particle swarm optimization algorithm applied in project under different parameters as well as the effects of the particle swarm optimization algorithm and the modified particle swarm optimization algorithm under identical updating parameter at the same time, we concluded that the precision of he modified particle swarm optimization algorithm is nicer than the particle swarm optimization algorithm. And the more parameters of structure are used to updating by the algorithm ,the nicer updating precision we will get.