Application of Adaptive Wavelet Transform based Multiple Analytical Mode Decomposition for Damage Progression Identification of Cable-Stayed Bridge via Shake Table Test


Extracting useful information (damage existence, location, identification, and quantification) from measured signals for damage identification is critical in structural health monitoring, while time-varying nature of most signals often require huge efforts. In this paper, adaptive wavelet analysis AWT is first introduced as a preprocessing approach of clearer, smoother and more accurate time–frequency representation. Optimized analytical mode decomposition (AMD) is then utilized for signal component extraction, with the help of AWT for bisecting frequency determination. Examples of time-varying signals of sinusoidal function and Duffing systems are used to illustrate the advantages of the algorithm, which proves to be successful in signal decomposition. Multiple AMD (MAMD) with the optimized algorithm is then utilized together with AWT for signal decomposition and system identification of the shake table test of a 1/20-scale cable-stayed bridge model. The extracted stiffness and damping coefficients retain a preliminary indication of the damage progression during the earthquake input.


Civil, Architectural and Environmental Engineering

Research Center/Lab(s)

INSPIRE - University Transportation Center


Financial support was provided by the U.S. National Science Foundation (Award No. CMMI1538416), National Natural Science Foundation of China (Award No. 51478338), and National Basic Research Program of China “973 Program” (Award No. 2013CB036302).

Keywords and Phrases

Adaptive algorithm; Cable-stayed bridge; Hilbert transform; Shake table test; Signal processing; System identification; Wavelet transform

International Standard Serial Number (ISSN)

0888-3270; 10961-216

Document Type

Article - Journal

Document Version


File Type





© 2020 Elsevier Ltd, All rights reserved.

Publication Date

15 Feb 2021