Parameter identification of periodical signals: Application to measurement and analysis of ocean wave forces

Abstract

This article presents an approach based on state observers to identify the parameters of an unknown periodic force exerted on a mechanical system. This approach comprises two stages and can be executed in real time by using only displacement measurements. The first stage goal is the estimation of the coefficients of a Fourier series that approximates the periodic force. From the estimated coefficients, the phase and the amplitude of the signal can be simultaneously computed; and from the estimated force, in a second stage, the frequencies of the signal can be estimated. To perform the tasks at each stage, two state observers were designed. To show the applicability of the proposed approach, the reconstruction of a wave force affecting a marine structure as well as the computation of the amplitude and phase of its spectral components was taken as case of study. The performance of the state observer was examined by means of simulations and off-line tests carried out with experimental data. Such data were obtained by executing laboratory tests and measuring waves in the Caribbean sea.

Applications of the integral equation method on nonlinear multi degree of freedom vibration systems

“…The modified (G’/G)-expansion method (Ahmad et al (2021)) is utilized to the nonlinear predator–prey system, the authors describe two-dimensional, three-dimensional, and contour shapes to show more physical and dynamic features of the answers obtained. According to the Fourier series of approximate periodic force, the state observer (Coronel-Escamilla,et al (2018); Torres,et al, (2017, 2018)) is designed to estimate the periodic force applied to the mechanical system. Omar Bazighifan and Hijaz Ahmad (Bazighifan,et al (2020)) studied the asymptotic form of the fourth-order advanced differential equations with delayed arguments, and their main idea is the theory of comparison with first and second-order delay equations and the Riccati substitution.…”

A Comprehensive Fault Diagnosis Method for Rolling Bearings Based on Refined Composite Multiscale Dispersion Entropy and Fast Ensemble Empirical Mode Decomposition

“…As bearings operate, they unavoidably suffer from cracks, corrosion, spalling and other factors, which cause the vibration signals to exhibit nonlinear dynamic characteristic. Therefore, how to effectively extract and detect fault characteristics of bearings is crucial in fault diagnosis [ 5 ]. Data-driven based methods are the mainstream methods for solving various problems [ 6 , 7 ], including statistical methods, signal processing methods, and artificial intelligence-based methods.…”

Parameter estimation algorithm for multivariable controlled autoregressive autoregressive moving average systems

“…Exploring valid methods is the eternal theme of the parameter estimation [11,12,13,14]. Recently, Torres et al proposed an approach based on state observers to identify the parameters of an unknown periodic force exerted on a mechanical system [15]. The approach can be described as two stages, the one is to obtain the estimates of the coefficients of a Fourier series that approximates the periodic force, and the other one is to get the frequencies of the signal.…”