Paper
1 April 2015 Damage detection and quantification in a structural model under seismic excitation using time-frequency analysis
Author Affiliations +
Abstract
In civil engineering, health monitoring and damage detection are typically carry out by using a large amount of sensors. Typically, most methods require global measurements to extract the properties of the structure. However, some sensors, like LVDT, cannot be used due to in situ limitation so that the global deformation remains unknown. An experiment is used to demonstrate the proposed algorithms: a one-story 2-bay reinforce concrete frame under weak and strong seismic excitation. In this paper signal processing techniques and nonlinear identification are used and applied to the response measurements of seismic response of reinforced concrete structures subject to different level of earthquake excitations. Both modal-based and signal-based system identification and feature extraction techniques are used to study the nonlinear inelastic response of RC frame using both input and output response data or output only measurement. From the signal-based damage identification method, which include the enhancement of time-frequency analysis of acceleration responses and the estimation of permanent deformation using directly from acceleration response data. Finally, local deformation measurement from dense optical tractor is also use to quantify the damage of the RC frame structure.
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Chun-Kai Chan, Chin-Hsiung Loh, and Tzu-Hsiu Wu "Damage detection and quantification in a structural model under seismic excitation using time-frequency analysis", Proc. SPIE 9437, Structural Health Monitoring and Inspection of Advanced Materials, Aerospace, and Civil Infrastructure 2015, 94372L (1 April 2015); https://doi.org/10.1117/12.2083924
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KEYWORDS
Autoregressive models

Error analysis

Earthquakes

Data modeling

Time-frequency analysis

Principal component analysis

Sensors

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