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Proceedings Paper

Detecting seismic response signals using singular spectrum analysis
Author(s): Chin-Hsiung Loh; Chia-Hui Chen; Chien-Hong Mao
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Paper Abstract

Singular Spectrum Analysis (SSA) is a novel non-parametric technique based on principle of multivariate statistics. The original time series is decomposed into a number of additive time series, each of which can be easily identified as being part of the modulated signals, or as being part of the random noise. It shows that the embedding dimension m of a dynamical time series can be conducted by the Singular Value Decomposition (SVD) experiments. This SVD scheme was used to detect low-dimensionally dynamic signals and the residuals. It provides trend extraction involves a decomposition of a time series into low-frequency trends and high-frequency variability. In this study, first, SSA is used to decompose the nonlinear seismic responses of reinforced concrete frames and to elucidate permanent deformation. Then, damage feature extraction is conducted using the high-frequency variability of SSA to identify the occurrence of damage. Comparison the results with the Holder exponent and the Level-1 detail of the discrete wavelet component to detect the damage occurrence was made. Finally, using SSA to estimate the permanent deformation using recorded acceleration data was also discussed. In this study, four reinforced concrete frame test data collected in response to various degrees of seismic excitation are used to demonstrate the application of SSA in damage detection.

Paper Details

Date Published: 31 March 2010
PDF: 12 pages
Proc. SPIE 7647, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2010, 76471S (31 March 2010); doi: 10.1117/12.846427
Show Author Affiliations
Chin-Hsiung Loh, National Taiwan Univ. (Taiwan)
Chia-Hui Chen, National Taiwan Univ. (Taiwan)
Chien-Hong Mao, National Taiwan Univ. (Taiwan)

Published in SPIE Proceedings Vol. 7647:
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2010
Masayoshi Tomizuka, Editor(s)

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