Structural Dynamic Model Updating Based On Ant Colony Optimization

Since the 1950s, Finite Element Analysis(FEA) and Experimental Modal Analysis(EMA) have become essential steps in the industries of aviation, aerospace, automobile, civil engineering, shipbuilding and so on. However, in most cases, results obtained with the FEA are not fit with those obtained with EMA. Under these circumstances, model updating is needed to get a correct predict to the behavior of the structure. In this thesis, the development of structural model updating is introduced first. As ant colony algorithm is to be used in this thesis, its introduction, development and its application in engineering are also introduced in detail. Then, this thesis puts forward a structural model updating method based on ant colony optimization, and Adaptive Ant Colony Algorithm (AACA) for continuous space optimization, a kind of ant colony optimization algorithm, is used in the updating of the finite element model of the Humen suspension bridge. And the thesis holds that the effect of the model updating is good by comparing the calculated modal data after model updating with before. The results of this thesis are compared with those of another two papers. This thesis concludes that the average errors after updating with the method in this thesis are smaller. Moreover, intermediate process of the algorithm is analyzed in detail and the thesis finds that its self-adjustment mechanism, its search mechanism and its adaptability are all playing their own roles effectively. Finally, the settings of the algorithm parameters are analyzed and the thesis holds that good efficiency and good effectiveness may be obtained when the settings are changed properly.