Nonlinearity Detection and Identification Using Discrete-Time Volterra Series: Application to a Solar Array Structure

Abstract

The aim of this paper is to identify a nonlinear model using time responses obtained from a sine sweep excitation applied to a simplif ied solar array structure. The nonlinearity is mainly caused by impacts, gaps and friction between the clamped interfaces of adjacent panels. A nonparametric model is identif ied using Volterra series, where the kernels are expanded with Kautz functions in order to decrease the problems associated with convergence and number of samples. The multiple convolutions provided by the Volterra kernels are used to propose a decision criterion based on a threshold limit to detect the level of linear or nonlinear behavior. The approach is also able to separate the linear and nonlinear contributions of the measured total response. The application performed in the experimental setup demostrates that the proposed method is successful in identifying the main nonlinear mechanism involved, despite of the complicated nature of the nonlinear system investigated.