Simultaneous identification of structural parameters and dynamic input with incomplete output‐only measurements

SUMMARY A hybrid heuristic optimization strategy is presented to simultaneously identify structural parameters and, when possible, dynamic input time histories from incomplete sets of output measurements. The proposed strategy combines a novel swarm intelligence algorithm, the artificial bee colony algorithm, with a local search operator, Nelder–Mead simplex method, integrated in a search space reduction approach, so as to improve the convergence efficiency of the overall identification process. Because of the independent nature of the algorithm, a parallel scheme is implemented so as to improve the computational efficiency. If the time histories of the structural response and information about the mass of the structural system are available, then the algorithm can also be used for the identification of the time histories of the dynamic input force through a modified Newmark integration scheme, using the current estimates of the structural parameters. To investigate the applicability of the proposed technique, three numerical examples, two shear-type building models and a coupled building system model under different conditions of data availabilities and noise corruption levels are presented. The results show that the proposed technique is powerful, robust and efficient in the simultaneous identification of the structural parameters and input force even from an incomplete set of noise-contaminated structural response measurements. Copyright © 2013 John Wiley & Sons, Ltd.

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