Nonlinear Parameteric Health Monitoring for Vibrating Structures Under Non-Stationary Excitation

Nonlinear system identification has been used to predict and monitor cracks as they form, propagate, and eventually cause the catastrophic failure of a vibrating cantilevered beam. The Continuous Time based system identification technique allows for estimation of model parameters based on collected stimulus and response data. For this study the estimated cubic stiffness term in the model is mapped as a function of time. The purpose of this investigation is to strengthen results from a previous study [1] through repetition, and to expand the scope of this system identification technique. This study mainly explores the effectiveness of using nonstationary excitation in the identification process, with an understanding that in implementation on real systems the selection input amplitude and frequency may not be readily controlled. Additionally, the robustness of this method is demonstrated in direct comparison to a wellaccepted linear-based approach. The results show this method to be successful with little prior knowledge of the accurate model form or parametric values for the systems being studied.

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