Operational modal analysis using time-frequency stochastic system identification
Journal
SHMII 2017 - 8th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Proceedings
Pages
737-745
Date Issued
2017
Author(s)
Abstract
Structural health monitoring assesses structural integrity by observing vibration responses of structures. Operational modal analysis is one of structural health monitoring approaches aiming at extracting the dynamic characteristics of structures from the vibration responses when these structures are under their operating conditions. These characteristics include natural frequencies, damping ratios, and mode shapes. Deviations in these characteristics represent the changes in structural properties and also imply possible damage to structures. In this study, a new operational modal analysis is proposed using stochastic subspace system identification based on multivariate time-frequency distributions. These time-frequency distributions are computed from the short-time Fourier transform, and a time-frequency matrix is subsequently obtained by stacking these distributions with respect to time. As the derivation in the data-driven stochastic subspace system identification, the future time-frequency matrix is projected onto the past time-frequency matrix. By exploiting the singular value decomposition, the system and measurement matrices of a stochastic state-space representation are derived. Consequently, the dynamic characteristics of a structure are extracted. As compared to the time-domain stochastic subspace system identification, the proposed method utilizes the past and future matrices with a lower dimension in projection. A spectral magnitude envelope can be applied to the time-frequency matrix to highlight the major frequency components as well as to eliminate the components with less influence. To demonstrate the effectiveness of the proposed method, both simulation and experimental data are employed to derive dynamic characteristics of structures. The proposed method is also compared with other operational modal analysis methods such as the stochastic subspace identification and frequency domain decomposition. As seen in the result, the proposed method is superior to the conventional methods, in particular of the dynamic characteristics at higher modes. ? 2017 International Society for Structural Health Monitoring of Intelligent Infrastrucure. All rights reserved.
Subjects
Domain decomposition methods; Frequency domain analysis; Identification (control systems); Modal analysis; Religious buildings; Singular value decomposition; State space methods; Stochastic systems; Structural analysis; Structural health monitoring; Vibration analysis; Dynamic characteristics; Frequency components; Frequency domain decomposition; Operational modal analysis; Short time Fourier transforms; State space representation; Stochastic subspace identification; Time-frequency distributions; Time domain analysis
Type
conference paper