46. Automated Modal Analysis Based on Statistical Evaluation of Frequency Responses

This paper presents a newly developed method for obtaining the modal model with a proper model order from experimental frequency response functions (FRF). The method is a multi-step procedure which commences with the identification of a high-order state-space model, Exhaustive Model (EM), using the full FRF data set. Then, modal states that give small contribution to the output, quantified by a metric associated to the observability grammian, are rejected from the EM resulting in a Reference Model (RM). Competing models, with the same model order as the RM, are then found by bootstrapping realization using same-size fractions of the full FRF. Eigensolutions of the Bootstrapping Models (BMs) are then paired by the eigensolutions of the RM based on high Modal Observability Correlation (MOC) indices. In a second reduction stage, the modal states with low MOC index are rejected from the BMs. Final model is found by an averaging through BMs. Only one threshold quantity, related to observability grammians need to be set by the user. The method thus requires very little user interaction. The method is applied to experimental data used in a previous IMAC Round Robin exercise for experimental modal analysis evaluation.