Abstract
A common practice for evaluating the nonlinear damping in ship roll motion is to perform a free-decay experiment. Although various methods have been developed to estimate the coefficients of a nonlinear damping model, these methods are limited to certain and relatively simple models. In addition, the performances of these methods have been greatly affected by the random noise embedded in the measured data. In this article, an efficient and versatile parameter identification method, applicable to rather general nonlinear damping and restoring models, to estimate nonlinear damping coefficients from contaminated free-decay data is proposed. The proposed method approximates the roll motion as complex exponentials by using the Prony-SS method. Because the Prony-SS method has a build-in noise rejection mechanism via the usage of truncated singular value decomposition, random noise in the measured data could be largely removed. Based on the analytical complex exponential representation of free-decay data, the damping coefficients can be easily estimated from the nonlinear equation of roll motion by using a least-square technique. Numerical examples demonstrate the effectiveness of the proposed method, even when the simulated data are significantly corrupted by random noise. Furthermore, the developed method performs well when nonlinear restoring parameters are also treated as unknown.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have