This paper presents the identification of structural systems under tri-directional seismic excitations using a statistically refined Bouc-Wen model of tri-axial interaction. Through limited vibration measurements in the National Center for Research on Earthquake Engineering in Taiwan, the Bouc-Wen model has been statistically and repetitively refined using the 95% confidence interval of the estimated structural parameters so as to determine their statistical significance in a multiple regression setting. The effectiveness of the refined model has been shown considering the effects of the sampling error, of the coupled restoring forces in tri-directions, and of the under-over-parameterization of structural systems. Sifted and estimated parameters such as the stiffness, and its corresponding natural frequency, resulting from the methodology developed in this paper are carefully observed 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
Identification of Structural Systems Under Tri-Directional Seismic Excitations Using a Statistically Refined Bouc-Wen Model
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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Wen-Shin Chen
Wen-Shin Chen
Feng Chia University, Taichung, Taiwan
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Jeng-Wen Lin
Feng Chia University, Taichung, Taiwan
Chong-Shien Tsai
Feng Chia University, Taichung, Taiwan
Wen-Shin Chen
Feng Chia University, Taichung, Taiwan
Paper No:
PVP2007-26136, pp. 133-138; 6 pages
Published Online:
August 20, 2009
Citation
Lin, J, Tsai, C, & Chen, W. "Identification of Structural Systems Under Tri-Directional Seismic Excitations Using a Statistically Refined Bouc-Wen Model." Proceedings of the ASME 2007 Pressure Vessels and Piping Conference. Volume 8: Seismic Engineering. San Antonio, Texas, USA. July 22–26, 2007. pp. 133-138. ASME. https://doi.org/10.1115/PVP2007-26136
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