Uncertainty analysis in Volterra series applied in a nonlinear system
Résumé
The goal of this paper is to verify the influence of uncertainties in the identification of Volterra kernels applied in a single degree-of-freedom nonlinear model with cubic stiffness. Stochastic modelling and Monte-Carlo simulations were performed for the identification of the Volterra kernels considering variations in the parameters of the motion equations, with the aim of verify how the kernels change with the presence of uncertainties. The results are evaluated by establishing confidence intervals in the kernels. These results allow to propose a statistical decision if the the kernels are representative of the nonlinear behavior of the systems even with uncertainties
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