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Mathematical Problems in Engineering
Volume 2014, Article ID 391815, 12 pages
http://dx.doi.org/10.1155/2014/391815
Research Article

An Extended Time Series Algorithm for Modal Identification from Nonstationary Ambient Response Data Only

1Experimental Facility Division, National Synchrotron Radiation Research Center, Hsinchu 30076, Taiwan
2Department of Aeronautics and Astronautics, National Cheng Kung University, Tainan 70101, Taiwan
3Instrumentation Development Division, National Synchrotron Radiation Research Center, Hsinchu 30076, Taiwan

Received 10 March 2014; Revised 17 June 2014; Accepted 26 June 2014; Published 17 July 2014

Academic Editor: Jaromir Horacek

Copyright © 2014 Chang-Sheng Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. F. Shen, M. Zheng, D. Feng Shi, and F. Xu, “Using the cross-correlation technique to extract modal parameters on response-only data,” Journal of Sound and Vibration, vol. 259, no. 5, pp. 1163–1179, 2003. View at Publisher · View at Google Scholar · View at Scopus
  2. W. Ren, W. Zatar, and I. E. Harik, “Ambient vibration-based seismic evaluation of a continuous girder bridge,” Engineering Structures, vol. 26, no. 5, pp. 631–640, 2004. View at Publisher · View at Google Scholar · View at Scopus
  3. C. Lin and D. Chiang, “Modal identification from nonstationary ambient response data using extended random decrement algorithm,” Computers and Structures, vol. 119, pp. 104–114, 2013. View at Publisher · View at Google Scholar · View at Scopus
  4. D. Chiang and C. Lin, “Identification of modal parameters from nonstationary ambient vibration data using correlation technique,” AIAA Journal, vol. 46, no. 11, pp. 2752–2759, 2008. View at Publisher · View at Google Scholar · View at Scopus
  5. G. E. P. Box, G. M. Jenkins, and G. C. Reinsel, Time Series Analysis: Forecasting and Control, Prentice Hall, Englewood Cliffs, NJ, USA, 3rd edition, 1994. View at MathSciNet
  6. S. M. Moore, J. C. S. Lai, and K. Shankar, “ARMAX modal parameter identification in the presence of unmeasured excitation-I: theoretical background,” Mechanical Systems and Signal Processing, vol. 21, no. 4, pp. 1601–1615, 2007. View at Publisher · View at Google Scholar · View at Scopus
  7. S. M. Moore, J. C. S. Lai, and K. Shankar, “ARMAX modal parameter identification in the presence of unmeasured excitation-II: numerical and experimental verification,” Mechanical Systems and Signal Processing, vol. 21, no. 4, pp. 1616–1641, 2007. View at Publisher · View at Google Scholar · View at Scopus
  8. S. M. Pandit and S. M. Wu, Time Series and System Analysis with Applications, John Wiley & Sons, New York, NY, USA, 1983.
  9. S. M. Pandit and N. P. Mehta, “Data dependent systems approach to modal analysis via state space,” Journal of Dynamic Systems, Measurement and Control, vol. 107, no. 2, pp. 132–138, 1985. View at Publisher · View at Google Scholar · View at Scopus
  10. S. M. Pandit and N. P. Mehta, “Data dependent systems approach to modal analysis Part 1. Theory,” Journal of Sound and Vibration, vol. 122, no. 3, pp. 413–422, 1988. View at Publisher · View at Google Scholar · View at Scopus
  11. M. Shinozuka, “Simulation of multivariate and multidimensional random processes,” Journal of the Acoustical Society of America, vol. 49, no. 1, pp. 357–367, 1971. View at Publisher · View at Google Scholar
  12. N. M. Newmark, “A method of computation for structural dynamics,” Journal of the Engineering Mechanics Division, vol. 85, no. 3, pp. 67–94, 1959. View at Google Scholar