Nonlinear model updating methodology with application to the IMAC XXXIII round robin benchmark problem

Abstract

We develop a new nonlinear model updating strategy based on global/local nonlinear system identification of general mechanical systems. The approach relies on analyzing system time series in the frequency-energy domain by constructing Hamiltonian, and forced/damped frequency-energy plots (FEPs). The system parameters are then characterized and updated by matching the backbone branches of the FEPs with the frequency-energy wavelet transforms of experimental and/or computational time series. The main advantage of this method is that no nonlinearity model is assumed a priori, and the system model is updated solely based on simulation and/or experimental results. By matching the frequency-energy plots of the benchmark system and its reduced order model, we show that we are able to retrieve the global dynamics in the frequency and energy ranges of interest, identify bifurcations, characterize local nonlinearities, and accurately reconstruct time series.