International Journal of Applied Science and Engineering
Published by Chaoyang University of Technology

Chern-Hwa Chena1 and Chia-I Oub

a Department of Civil and Environmental Engineering, National University of Kaohsiung, Kaohsiung, Taiwan 81148.
b Department of Civil Engineering, National Chiao Tung University, Hsinchu, Taiwan 30010.


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ABSTRACT


This paper utilizes a continuous wavelet transform algorithm to identify the dynamic parameters of a cable-stayed bridge under normal traffic and environmental wind fields. The dynamic characteristics were determined by using an identification technique for the Kao Ping Hsi cable-stayed bridge. The modal parameters identified from the field vibration tests were compared with those used in the finite element analysis. The finite element model can then be refined by the experimental results. Next, a comparison between the identified results and the updating finite element results shows reasonable agreements for the first several modes in the two directions, namely, vertical, and transverse directions. Finally, the rational finite element model of Kao Ping Hsi cable-stayed bridge can be established. The finite element model obtained herein were used as the damage index for monitoring the long-term safety of the Kao Ping Hsi cable-stayed bridge under environmental loads in the future.


Keywords: cable-stayed bridge; field test; modal identification; wavelet transform.


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REFERENCES


  1. [1] Chen, C. H., Lu, L. Y., and Yang, Y. B. 1997. Dynamic testing and system identification of a highway bridge. Journal of Structural Engineering, Taipei, Taiwan, 12, 3: 3-22.in Chinese.

  2. [2] Chen, C. H. 2005. Structural identification from field measurement data using a neural network. Journal of Smart Materials and Structures, 14: S104-S115.

  3. [3] Huang, C. S. 2001. Structural identification from ambient vibration measurement using the multivarible AR model. Journal Sound and Vibration, 241, 3: 337-359.

  4. [4] Huang, C. S., Hung, S. L., Lin, C. J., and Su, W. C. 2005. A wavelet-based approach to identifying structural modal parameters from seismic response and free vibration data. Computer-Aided Civil and Infrastructure Engineering, 20: 408-423.

  5. [5] Huang, C. S., and Su, W. C. 2007. Identification of modal parameters of a time invariant linear system by continuous wavelet transformation. Mechanical Systems and Signal Processing, 21: 1642-1664.

  6. [6] Chui, C. K. 1992. “An introduction to wavelets: wavelet analysis and its application volume 1”. Boston, Academic Press.

  7. [7] Huang, C. S. 2001. Structural identification from ambient vibration measurement using the multivariate AR model. Journal of Sound and Vibration, 241, 3: 337-359.

  8. [8] Daubechies, I. 1992. “Ten lectures on wavelets”. SIAM, Philadelphia.

  9. [9] Yang, J. C. S., and Caldwell, D. 1976. Measurement of damping and the detection of damages in structures by the random decrement technique. Shock and Vibration Bulletin, 46: 129-136.

  10. [10] Allemang, R. L., and Brown, D. L. 1983. A correlation coefficient for modal vector analysis. Proceedings of the 1st International Modal Analysis Conference. Bethel, Connecticut, U. S. A. 110-116.


ARTICLE INFORMATION




Accepted: 2009-05-08
Available Online: 2009-02-01


Cite this article:

Chen, C.-H., Ou, C.-I. 2009. Modal identification from field test and FEM updating of a long span Cable-Stayed bridge. International Journal of Applied Science and Engineering, 6, 251–262. https://doi.org/10.6703/IJASE.2009.6(3).251