This paper proposes a statistical confidence interval based model updating approach for the health diagnosis of structural systems subjected to seismic excitations. The proposed model updating approach uses the 95% confidence interval of the estimated structural parameters to determine their statistical significance in a least-squares regression setting. When the parameters’ confidence interval covers the “null” value, it is statistically sustainable to truncate such parameters. The remaining parameters will repetitively undergo such parameter sifting process for model updating until all the parameters’ statistical significance cannot be further improved. This newly developed model updating approach is implemented for the developed series models of multivariable polynomial expansions: the linear, the Taylor series, and the power series model, leading to a more accurate identification as well as a more controllable design for system vibration control.
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ASME 2007 Pressure Vessels and Piping Conference
July 22–26, 2007
San Antonio, Texas, USA
Conference Sponsors:
- Pressure Vessels and Piping Division
ISBN:
0-7918-4286-X
PROCEEDINGS PAPER
Health Diagnosis of Structural Systems Using a Repetitive Model Updating Approach
Jeng-Wen Lin,
Jeng-Wen Lin
Feng Chia University, Taichung, Taiwan
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Chong-Shien Tsai,
Chong-Shien Tsai
Feng Chia University, Taichung, Taiwan
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Chih-Wei Huang
Chih-Wei Huang
Feng Chia University, Taichung, Taiwan
Search for other works by this author on:
Jeng-Wen Lin
Feng Chia University, Taichung, Taiwan
Chong-Shien Tsai
Feng Chia University, Taichung, Taiwan
Chih-Wei Huang
Feng Chia University, Taichung, Taiwan
Paper No:
PVP2007-26134, pp. 105-110; 6 pages
Published Online:
August 20, 2009
Citation
Lin, J, Tsai, C, & Huang, C. "Health Diagnosis of Structural Systems Using a Repetitive Model Updating Approach." Proceedings of the ASME 2007 Pressure Vessels and Piping Conference. Volume 8: Seismic Engineering. San Antonio, Texas, USA. July 22–26, 2007. pp. 105-110. ASME. https://doi.org/10.1115/PVP2007-26134
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