Modal analysis of slow varying non-stationary vibration by model updating with Schur complement

• Published in: Mechanical systems and signal processing Vol. 162; p. 108022
• Main Authors: Bui, Thi-Thuyet, Vu, Viet-Hung, Liu, Zhaoheng
• Format: Journal Article
• Language: English
• Published: Berlin Elsevier Ltd 01.01.2022; Elsevier BV
• Subjects: Algorithms; Autoregressive model; Autoregressive models; Excitation; Fourier transforms; Least squares method; Modal analysis; Model order selection; Model parameter identification; Model updating; Parameters; Recursive least squares; Sliding window; Steel plates; Varying system; Vibration analysis; Vibration monitoring; Varying system; Autoregressive model; Model order selection; Model parameter identification; Recursive least squares; Sliding window
• ISSN: 0888-3270; 1096-1216
• DOI: 10.1016/j.ymssp.2021.108022

This paper proposes a new algorithm for the online monitoring of slow varying modal parameters in vibrating structures subjected to unknown excitations. In this method, an Auto-Regressive (AR) model will be applied in a Short-Time Sliding Window (STSW) on measured signals. The model parameters will be determined and updated through the order and time obtained from the previous computational window. The recursive multivariable least-squares method is utilized in conjunction with the Schur complement method to find solutions. Numerical simulations of the gradual changing system acted by the random excitations and sinusoidal force are presented. Finally, the modal parameters for the multichannel data measured on an experimental steel plate emerging from the water are identified and compared with those obtained with the analytical method and Short-Time Fourier Transform (STFT), providing a powerful means of validating the proposed method.