Application of Wavelet Analysis to the Damage Detection of RC Frame Structures
Date Issued
2007
Date
2007
Author(s)
Chen, I-An
DOI
en-US
Abstract
This study presents a set of feature extraction techniques for damage detection based on wavelet analysis, including continuous wavelet transform, discrete wavelet transform, and wavelet packet transform. Firstly, a brief introduction to wavelet analysis on the structural damage detection is presented. Secondly, a series of description on continuous wavelet transform, discrete wavelet transform, wavelet packet transform, Hilbert transform, and features extracted for damage detection, including Holder exponent, level-1 details function of DWT, Hilbert amplitude spectrum, Hilbert marginal spectrum, and phase index are presented. After that, these features are applied to numerical simulation data to verify their application to damage detection. The numerical simulation data are obtained by a simulation model which was first proposed by Sisvaselvan and Reinhorn (2000), and modified by S. H. Chao and C. H. Loh (2006). The simulation model, named deteriorating hysteretic model, can be used to numerically simulate the dynamic responses of a SDOF RC structural system. After verified by the application to numerical simulation data, these feature extraction techniques are applied to shaking table test data. The test specimens include a RC wall frame structure, and a three-story steel frame structure. The RC wall frame structure can be simplified as a single-degree-of-freedom structural system which is similar to the numerical simulation model mentioned above. The shaking table test of the three-story steel frame structure is studied to identify the abrupt change of stiffness in the first floor of the three-story steel frame structure. Analysis results show that these features, mentioned in this study, can be effectively used to detect structural damage only through the direct response measurement without any a priori knowledge of the original structural system. Based on the analysis results of feature extraction for damage detection, there is a conclusion in the end.
Subjects
小波
損壞識別
wavelet
damage detection
Type
thesis
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