Comparative study of model updating methods using simulated experimental data

The inverse eigensensitivity method and the response function method of analytical model updating have become relatively more popular among other methods and have been successfully applied to the practice of analytical model improvement. This paper gives a detailed comparison of these two approaches of model updating on the basis of computer simulated experimental data with the objective of studying the convergence of the two methods and the accuracy with which they predict the corrections required in a finite element model. The effect of the amount of experimental data used in the process of model improvement on the quality of an updated model is also studied. The test cases of complete, incomplete and noisy experimental data are considered. The updated models are compared on the basis of some error indices constructed to quantify error in the predicted natural frequencies, mode shapes and response functions