Abstract
This paper proposes basis functions based time domain Volterra model for nonlinear system identification. The Volterra kernels are expanded by using complex exponential basis functions and estimated via genetic algorithm (GA). The accuracy and practicability of the proposed method are then assessed experimentally from a scaled 1:100 model of a prototype truss spar platform. Identification results in time and frequency domain are presented and coherent functions are performed to check the quality of the identification results. It is shown that results between experimental data and proposed method are in good agreement.
Highlights
Floating structures is known as a structural system that exhibit significant nonlinear behavior [1,2]
By acquiring the measured time series of wave height and motion responses experimentally, empirical models could be derived to describe the dynamic behavior of the system
If the interest is in the amplitude and statistics of the floating structure motions, the empirical models are usually presented in term of transfer function (TF) or response amplitude operator (RAO) [3]
Summary
Floating structures is known as a structural system that exhibit significant nonlinear behavior [1,2]. Frequency resolution will be trade off in the TFs estimation Sometimes, it leads to untrustworthy, espescially for non-Gaussian wave. It leads to untrustworthy, espescially for non-Gaussian wave In this regard, the objective of this paper is to avoid the use of HOSA by using time-domain Volterra model as an alternative. The proposed method is named as basis functions based time domain Volterra model (BFVM) and applied to the floating structures as case study.
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