Time-Frequency Analysis and Applications in Time-Varying/Nonlinear Structural Systems: A State-of-the-Art Review
Abstract
Nonlinear dynamic behaviors of civil engineering structures have been observed not only under extreme loads but also during normal operations. Characterization of the time-varying property or nonlinearity of the structures must account for temporal evolution of the frequency and amplitude contents of nonstationary vibration responses. Neither time analysis nor frequency analysis method alone can fully describe the nonstationary characteristics. In this article, an attempt is made to review the milestone developments of time-frequency analysis in the past few decades and summarize the fundamental principles and structural engineering applications of wavelet analysis and Hilbert transform analysis in system identification, damage detection, and nonlinear modeling. This article is concluded with a brief discussion on challenges and future research directions with the application of time-frequency analysis in structural engineering.
Recommended Citation
Z. Wang et al., "Time-Frequency Analysis and Applications in Time-Varying/Nonlinear Structural Systems: A State-of-the-Art Review," Advances in Structural Engineering, vol. 21, no. 10, pp. 1562 - 1584, SAGE Publications, Jul 2018.
The definitive version is available at https://doi.org/10.1177/1369433217751969
Department(s)
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Damage detection; Dynamic response; Wavelet analysis; Wavelet transforms; Civil engineering structures; Future research directions; Hilbert transform; Non-stationary characteristics; Nonlinear dynamic behaviors; Nonlinearity; State-of-the art reviews; Time varying; Structural analysis; Time-varying; Time-frequency
International Standard Serial Number (ISSN)
1369-4332
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2018 The Authors, All rights reserved.
Publication Date
01 Jul 2018
Comments
This study was financially supported by the National Key R&D Program of China under grant no. 2017 YFC 0805100, by the National Natural Science Foundation of China under grant nos 51478159 and 51578206, by "The Fundamental Research Funds for the Central Universities," by the Natural Science Funds for Distinguished Young Scholar of Anhui province under grant no. 1708085J06, and by the US National Science Foundation under award no. CMMI1538416.