Model updating of a full-scale bridge structure using particle swarm optimization

Due to many idealized assumptions in the development of finite element (FE) models, the actual behavior of full scale structures often differs from model predictions. In model updating, dynamic characteristics, such as natural frequencies, mode shapes and damping ratios, are correlated with their FE model counterparts to calibrate the FE model. In this paper, particle swarm optimization (PSO), an evolutionary algorithm, has been investigated for dynamic model updating of full scale structures. The full scale bridge under study is a cable stayed pedestrian footbridge. The bridge comprises two spans with composite steel concrete deck and a centre steel tower. The bridge was excited using three dynamically synchronized shakers and a dense array of sensors was employed to measure the response. It was found from the updating results that PSO is successful in model updating of the full scale bridge giving physically meaningful results.