Application of an automated modal analysis based on frequency response function estimates

Paper in proceeding, 2012

Given measured data as estimated frequency responses of a quasi-linear system, there is a variety of system identification methods that identify a state-space model that gives good correlation to the data. Such methods are the N4SID and the PolyMAX methods. Using these methods, a key problem is to select the proper model order. An Automated Modal Analysis was developed in our group to find the proper model order. This method is based on the statistical evaluation of an ensemble of state-space models all identified from the same basic set of frequency response functions, but with different realizations based on a bootstrapping scheme. In this work, we made that method more robust and applied it to two real test data sets.