Table of Contents Author Guidelines Submit a Manuscript
Abstract and Applied Analysis
Volume 2014, Article ID 103102, 8 pages
http://dx.doi.org/10.1155/2014/103102
Research Article

Structural Stiffness Identification Based on the Extended Kalman Filter Research

1School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China
2Northeast Forestry University, Harbin 150040, China
3State Key Laboratory of Frozen Soil Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, CAS, Lanzhou 730000, China

Received 5 January 2014; Revised 24 March 2014; Accepted 27 March 2014; Published 21 May 2014

Academic Editor: Shuping He

Copyright © 2014 Fenggang Wang 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. H.-P. Zhu, J. Yu, and J.-B. Zhang, “A summary review and advantages of vibration-based damage identification methods in structural health monitoring,” Engineering Mechanics, vol. 28, no. 2, pp. 1–11, 2011. View at Google Scholar · View at Scopus
  2. H. Kim and H. Melhem, “Damage detection of structures by wavelet analysis,” Journal of Engineering Structures, vol. 26, pp. 7–14, 2004. View at Google Scholar
  3. J. P. Ou and G. Y. Wang, Random Vibration of Structures, Press of Higher Education, Beijing, China, 1998.
  4. O. S. Salawu, “Detection of structural damage through changes in frequency: a review,” Engineering Structures, vol. 19, no. 9, pp. 718–723, 1997. View at Google Scholar · View at Scopus
  5. F. Vestroni and D. Capecchi, “Damage detection in beam structures based on frequency measurements,” Journal of Engineering Mechanics, vol. 126, no. 7, pp. 761–768, 2000. View at Google Scholar · View at Scopus
  6. D. L. Zheng, Z. F. Li, and H. X. Hua, “Summary review of structural initial damage identification methods,” Journal of Vibration and Shock, vol. 21, no. 2, pp. 1–6, 2002. View at Google Scholar · View at Scopus
  7. S. Y. Du, X. G. Yin, and H. Chen, “Sieve method for identifying damage based on matrix perturbation theory,” Chinese Journal of Applied Mechanics, vol. 25, no. 1, pp. 75–78, 2008. View at Google Scholar · View at Scopus
  8. M. F. Elkordy, K. C. Chang, and G. C. Lee, “Application of neural networks in vibrational signature analysis,” Journal of Engineering Mechanics, vol. 120, no. 2, pp. 250–264, 1994. View at Google Scholar · View at Scopus
  9. H.-S. Tang, S.-T. Xue, R. Chen, and K. Jin, “Sequential LS-SVM for structural systems identification,” Journal of Vibration Engineering, vol. 19, no. 3, pp. 382–387, 2006. View at Google Scholar · View at Scopus
  10. S. P. He and J. Song, “Unbiased estimation of Markov jump systems with distributed delays,” Signal Processing, vol. 100, pp. 85–92, 2014. View at Publisher · View at Google Scholar
  11. S. P. He and F. Liu, “Robust finite-time estimation of Markovian jumping systems with bounded transition probabilities,” Applied Mathematics and Computation, vol. 222, pp. 297–306, 2013. View at Publisher · View at Google Scholar · View at MathSciNet
  12. S. P. He, “Resilient L2-L filtering of uncertain Markovian jumping systems within the finite-time interval,” Abstract and Applied Analysis, vol. 2013, Article ID 791296, 7 pages, 2013. View at Google Scholar · View at MathSciNet
  13. S. P. He and F. Liu, “Robust peak-to-peak filtering for Markov jump systems,” Signal Processing, vol. 90, no. 2, pp. 513–522, 2010. View at Publisher · View at Google Scholar · View at Scopus
  14. S. P. He and F. Liu, “Adaptive observer-based fault estimation for stochastic Markovian jumping systems,” Abstract and Applied Analysis, vol. 2012, Article ID 176419, 11 pages, 2012. View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  15. A. K. Pandey, M. Biswas, and M. M. Samman, “Damage detection from changes in curvature mode shapes,” Journal of Sound and Vibration, vol. 145, no. 2, pp. 321–332, 1991. View at Google Scholar · View at Scopus
  16. W.-X. Ren and G. D. Roeck, “Structural damage identification using modal data. I: simulation verification,” Journal of Structural Engineering, vol. 128, no. 1, pp. 87–95, 2002. View at Publisher · View at Google Scholar · View at Scopus
  17. J. G. Sun, “Least-squares solutions of a class of inverse eigenvalue problems,” Mathematica Numerica Sinica, vol. 9, no. 2, pp. 206–216, 1987. View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  18. M. F. Elkordy, K. C. Chang, and G. C. Lee, “Application of neural networks in vibrational signature analysis,” Journal of Engineering Mechanics, vol. 120, no. 2, pp. 250–265, 1994. View at Google Scholar · View at Scopus
  19. H.-S. Tang, S.-T. Xue, R. Chen, and K. Jin, “Sequential LS-SVM for structural systems identification,” Journal of Vibration Engineering, vol. 19, no. 3, pp. 382–387, 2006. View at Google Scholar · View at Scopus
  20. B. Liu, “Uncertain set theory and uncertain inference rule with application to uncertain control,” Journal of Uncertain Systems, vol. 4, pp. 83–98, 2010. View at Google Scholar
  21. B. Liu, “Some research problems in uncertainty theory,” Journal of Uncertain Systems, vol. 3, pp. 3–10, 2009. View at Google Scholar
  22. G. D. Tian, M. C. Zhou, and J. W. Chu, “A chance constrained programming approach to determine the optimal disassembly sequence,” IEEE Transactions on Automation Science and Engineering, vol. 10, pp. 1004–1013, 2013. View at Google Scholar
  23. G. Tian, M. Zhou, J. Chu, and Y. Liu, “Probability evaluation models of product disassembly cost subject to random removal time and different removal labor cost,” IEEE Transactions on Automation Science and Engineering, vol. 9, no. 2, pp. 288–295, 2012. View at Publisher · View at Google Scholar · View at Scopus
  24. B. S. Zhou and W. S. Zhu, “Study on forecasting the parameters of roadway surrounding rock based by artificial neural networks,” Rock and Soil Mechanics, vol. 20, no. 1, pp. 22–26, 1999. View at Google Scholar · View at Scopus
  25. S. F. Masri, J. P. Caffrey, T. K. Caughey, A. W. Smyth, and A. G. Chassiakos, “Identification of the state equation in complex non-linear systems,” International Journal of Non-Linear Mechanics, vol. 39, no. 7, pp. 1111–1127, 2004. View at Publisher · View at Google Scholar · View at Scopus
  26. H. M. Chen, G. Z. Qi, J. C. S. Yang, and F. Amini, “Neural network for structural dynamic model identification,” Journal of Engineering Mechanics, vol. 121, no. 12, pp. 1377–1381, 1995. View at Google Scholar · View at Scopus
  27. M. Nakaimra, S. F. Masri, and T. K. Caughey, “A method for non parametric: damage detection through the use of neural networks,” Earthquake Engineering & Structural Dynamics, vol. 27, pp. 997–1010, 1998. View at Google Scholar
  28. S. F. Masri, N. F. Hunter, and A. G. Chassiakos, “Application of neural networks for detection of nonlinear systems,” Engineering Mechanics, vol. 126, pp. 666–676, 2000. View at Publisher · View at Google Scholar
  29. Y.-H. An and J.-P. Ou, “Experimental and numerical studies on precise damage localization of a long-span steel truss bridge model,” Chinese Journal of Computational Mechanics, vol. 28, no. 5, pp. 730–736, 2011. View at Google Scholar · View at Scopus
  30. J. L. Hou, J. P. Ou, and L. Jankowski, “The study and experiment of substructure damage identification based on local primary frequency,” Engineering Mechanics, vol. 29, pp. 99–105, 2012. View at Google Scholar
  31. C. Zhang, G.-Q. Song, and G.-Y. Wu, “Structure damage identification by finite element model updated with improved Tikhonov regularization,” Engineering Mechanics, vol. 29, no. 2, pp. 29–44, 2012. View at Google Scholar · View at Scopus
  32. X. D. Sun, J. P. Ou, G. L. Hou et al., “Damage Identification based on Bayesian fusion of global and local information,” Engineering Mechanics, vol. 29, pp. 234–239, 2012. View at Google Scholar
  33. Q. P. Wang and X. Guo, “DLV-based research on damage identification of steel frame,” World Earthquake Engineering, vol. 28, pp. 50–55, 2012. View at Google Scholar
  34. C. Deng, P.-Y. Gu, and L. Tang, “Damage diagnosis based on natural frequencies of a structure by adding known masses,” Journal of Vibration and Shock, vol. 29, no. 7, pp. 135–138, 2010. View at Google Scholar · View at Scopus