Paper
31 March 2010 Detecting seismic response signals using singular spectrum analysis
Chin-Hsiung Loh, Chia-Hui Chen, Chien-Hong Mao
Author Affiliations +
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.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chin-Hsiung Loh, Chia-Hui Chen, and Chien-Hong Mao "Detecting seismic response signals using singular spectrum analysis", Proc. SPIE 7647, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2010, 76471S (31 March 2010); https://doi.org/10.1117/12.846427
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Cited by 2 scholarly publications.
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KEYWORDS
Signal detection

Spectrum analysis

Damage detection

Feature extraction

Interference (communication)

Signal processing

Structural health monitoring

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