An Iterative Procedure for Model Updating Based on Selective Sensitivity

Model updating of a structural system may require a large number of parameter to be identified simultaneously. Due to the ill-conditionedness, large errors in identified parameter values will occur when errors are present in the measurements. One solution for this problem is using the concept of selective sencitivity [1]. The method allows to reduce ill-conditioning by providing specific excitations causing model responses sensitive to a small number of model parameters. Thus, only a few parameters are estimated at a time. However, defining such excitations generally involves the knowledge of all parameters to be identified. Therefore, an iterative experiment procedure is suggested (e.g the method of multi-hypothesis testing [2]) which is normally a time-consuming process.