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Journal of Sensors
Volume 2015, Article ID 246480, 6 pages
Research Article

A Practical Method for Grid Structures Damage Location

1Transportation Equipment and Marine Engineering College, Dalian Maritime University, Dalian, Liaoning 116026, China
2Dalian University of Technology, Linggong Road No. 2, Integrated Building 4, 219-B, Dalian, Liaoning 116024, China

Received 29 September 2014; Revised 29 January 2015; Accepted 9 February 2015

Academic Editor: Christos Riziotis

Copyright © 2015 Zhefu Yu and Linsheng Huo. 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. D. J. Pines and A. E. Aktan, “Status of structural health monitoring of long-span bridges in the United States,” Progress in Structural Engineering and Materials, vol. 4, no. 4, pp. 372–380, 2002. View at Publisher · View at Google Scholar
  2. H. S. Sohn, C. R. Farrar, F. M. Hemez et al., A Review of Structural Health Monitoring Literature 1996–2001, Los Alamos National Laboratory, San Francisco, Calif, USA, 2003.
  3. S. Chen and G. Li, “Artificial neural networks in structural damage identification,” Vibration, Test and Damage, vol. 21, no. 2, pp. 116–124, 2001. View at Google Scholar
  4. M. Kaouk, D. C. Zimmerman, and T. W. Simmermacher, “Assessment of damage affecting all structural properties using experimental modal parameters,” Journal of Vibration and Acoustics, vol. 122, no. 4, pp. 456–463, 2000. View at Publisher · View at Google Scholar · View at Scopus
  5. S.-L. J. Hu, H. Li, and S. Wang, “Cross-model cross-mode method for model updating,” Mechanical Systems and Signal Processing, vol. 21, no. 4, pp. 1690–1703, 2007. View at Publisher · View at Google Scholar · View at Scopus
  6. A. Dixit and S. Hanagud, “Damage localization by isolating the part of the response due to the damage only,” Journal of Applied Mechanics, vol. 80, no. 1, Article ID 011015, 8 pages, 2012. View at Publisher · View at Google Scholar · View at Scopus
  7. M. R. Hernandez-Garcia, S. F. Masri, R. Ghanem, E. Figueiredo, and C. R. Farrar, “An experimental investigation of change detection in uncertain chain-like systems,” Journal of Sound and Vibration, vol. 329, no. 12, pp. 2395–2409, 2010. View at Publisher · View at Google Scholar · View at Scopus
  8. A. Alvandi and C. Cremona, “Assessment of vibration-based damage identification techniques,” Journal of Sound and Vibration, vol. 292, no. 1-2, pp. 179–202, 2006. View at Publisher · View at Google Scholar · View at Scopus
  9. J.-G. Han, W.-X. Ren, and Z.-S. Sun, “Wavelet packet based damage identification of beam structures,” International Journal of Solids and Structures, vol. 42, no. 26, pp. 6610–6627, 2005. View at Publisher · View at Google Scholar · View at Scopus
  10. E. Figueiredo, M. D. Todd, C. R. Farrar, and E. Flynn, “Autoregressive modeling with state-space embedding vectors for damage detection under operational variability,” International Journal of Engineering Science, vol. 48, no. 10, pp. 822–834, 2010. View at Publisher · View at Google Scholar · View at Scopus
  11. L. Liu and G. Meng, “Vector regression algorithm applied research in the beam structural damage diagnosis support,” Shock and Vibration, vol. 25, no. 3, pp. 99–100, 2006. View at Google Scholar
  12. Y. Zhefu, H. Linsheng, and Z. Lei, “Grid structure damage location base on cross-correlation function,” in Proceedings of the 4th International Conference on Civil Engineering, Architecture and Building Materials, pp. 1083–1086, May 2014.
  13. R. J. Allemang and D. L. Brown, “A correlation coefficient for modal vector analysis,” in Proceedings of the 1st International Modal Analysis Conference & Exhibit (IMAC '82), pp. 110–116, November 1982. View at Scopus
  14. L. Jiayan, Y. Qianfeng, L. Ying et al., “Experimental analysis of structural damage identification based on random vibration response of the cross-correlation function,” Vibration and Shock, vol. 30, no. 8, pp. 221–224, 236, 2011. View at Google Scholar
  15. V. N. Vapnik, The Nature of Statistical Learning Theory, Springer, New York, NY, USA, 1995. View at Publisher · View at Google Scholar · View at MathSciNet