Application of decoupled ARMA model to modal identification of linear time-varying system based on the ICA and assumption of "short-time linearly varying". (12th May 2021)

• Record Type: Journal Article
• Authors: Chen, Tengfei; Chen, Guoping; Chen, Weiting; Hou, Shuo; Zheng, Yuxuan; He, Huan
• Is Part Of: Journal of sound and vibration. Volume 499(2021)
• Publication Date: 2021-05-12
• Subjects: Linear time-varying structure -- Modal identification -- ARMA model -- "Short-time linearly varying" assumption -- ICA method; Sound -- Periodicals; Vibration -- Periodicals; Son -- Périodiques; Vibration -- Périodiques; Sound; Vibration; Periodicals; Electronic journals; 620.205
• DOI: 10.1016/j.jsv.2021.115997
• Languages: English
• ISSNs: 0022-460X

Abstract

Highlights: Decoupled ARMA model of time-varying linear dynamic system is established. "Short-time linearly varying" assumption is applied to system identification. The proposed method is validated by numerical and experimental study. Abstract: A new approach for time-varying (TV) modal parameters identification is proposed in this research. In the identification process, the entire signal is divided into successive short time windows, where the structure response under white noise excitation is transformed into modal coordinates by the Independent Component Analysis (ICA) method. The decoupled time-varying Auto-Regressive Moving-Average (ARMA) model based on the new assumption of "short-time linearly varying" (STLV) is established with the extracted modal coordinates. The TV parameters can be obtained by solving a nonlinear least squares problem. The main motivation of the proposed approach is to simplify the model and reduce the computational difficulty. The effectiveness and accuracy are validated via both the numerical example and experiment.