Singular Spectrum Analysis (SSA) is a novel technique and has proven to be a powerful tool for time data series analysis. It takes singular value decomposition (SVD) of Hankel matrix embedded by analyzed time data series and decomposes the data into several simple, independent and identifiable components. In this paper, first, the coupling degree of the 1st and 2nd singular values through the composition of the analyzed signal in SSA is used as two important values to detect damage. Besides, based on the extracted sub-space or null-space from SVD of analytic matrix, damage detection algorithm is developed by considering the orthonormality between the sub-space and null-space. The proposed algorithms are verified using non-stationary response data of a model bridge (data from scouring test of a bridge) and field experiment of a bridge during abnormal weather condition. Discussion on the proposed methods with different assessment method to identify the occurrence of damage using SSI-DATA and SSI-COV to identified the system dynamic characteristics are also made.
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ASME 2012 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
September 19–21, 2012
Stone Mountain, Georgia, USA
Conference Sponsors:
- Aerospace Division
ISBN:
978-0-7918-4509-7
PROCEEDINGS PAPER
Application of Singular Spectrum Analysis to Bridge Structure Health Monitoring and Damage Detection
Chin-Hsiung Loh,
Chin-Hsiung Loh
National Taiwan University, Taipei, Taiwan
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Shu-Hsien Chao
Shu-Hsien Chao
National Taiwan University, Taipei, Taiwan
Search for other works by this author on:
Chin-Hsiung Loh
National Taiwan University, Taipei, Taiwan
Shu-Hsien Chao
National Taiwan University, Taipei, Taiwan
Paper No:
SMASIS2012-7905, pp. 587-594; 8 pages
Published Online:
July 24, 2013
Citation
Loh, C, & Chao, S. "Application of Singular Spectrum Analysis to Bridge Structure Health Monitoring and Damage Detection." Proceedings of the ASME 2012 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation and Control of Adaptive Systems; Structural Health Monitoring. Stone Mountain, Georgia, USA. September 19–21, 2012. pp. 587-594. ASME. https://doi.org/10.1115/SMASIS2012-7905
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