Finite element model updating using operational modal analysis and bees optimization algorithm

In this study, application of operational modal analysis and bees algorithm (BA) in order finite element model updating are investigated. BA optimization algorithm applies instinctive behavior of honeybees for finding food sources. An objective function is defined as the sum of the squared errors between the obtained natural frequencies by operational modal analysis and finite element method. Experimental natural frequencies are determined by stochastic subspace identification (SSI) which is considered as one of the strong methods of operational modal analysis. In order to investigate the accuracy of the proposed method, BA and SSI methods are implemented on a three story structure to update parameters of its finite element model. Furthermore, to study of effectiveness of BA algorithm, the results of BA algorithm are compared with particle swarm optimization (PSO) and Nelder-Mead (NM) algorithms. The results show that the BA optimization algorithm, in comparison with the PSO and NM methods, is more accurate and faster to update finite element model.