About this Journal Submit a Manuscript Table of Contents
International Journal of Distributed Sensor Networks
Volume 2012 (2012), Article ID 798714, 11 pages
http://dx.doi.org/10.1155/2012/798714
Research Article

Structural Damage Information Fusion Based on Soft Computing

Beijing Laboratory of Earthquake Engineering and Structural Retrofit, Beijing University of Technology, Beijing 100124, China

Received 11 July 2012; Accepted 3 August 2012

Academic Editor: Liguo Zhang

Copyright © 2012 Haoxiang He 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. G. W. Housner, L. A. Bergman, T. K. Caughey et al., “Structural control: past, present, and future,” Journal of Engineering Mechanics, vol. 123, no. 9, pp. 897–971, 1997. View at Scopus
  2. D. L. Hall, Mathematical Techniques in Multi-Sensor Data Fusion, Artech House, 1992.
  3. S. F. Jiang, C. Fu, and C. Zhang, “A hybrid data-fusion system using modal data and probabilistic neural network for damage detection,” Advances in Engineering Software, vol. 42, no. 6, pp. 368–374, 2011. View at Publisher · View at Google Scholar · View at Scopus
  4. H. Y. Guo, “Structural damage detection using information fusion technique,” Mechanical Systems and Signal Processing, vol. 20, no. 5, pp. 1173–1188, 2006. View at Publisher · View at Google Scholar · View at Scopus
  5. M. H. O'Brien and M. J. Loughlin, “Displacement damage quantification in future fusion systems,” Fusion Engineering and Design, vol. 82, no. 15–24, pp. 2536–2542, 2007. View at Publisher · View at Google Scholar · View at Scopus
  6. H. Sohn and K. H. Law, “A Bayesian probabilistic approach for structure damage detection,” Earthquake Engineering and Structural Dynamics, vol. 26, no. 12, pp. 1259–1281, 1997. View at Scopus
  7. J. L. Beck and S. K. Au, “Bayesian updating of structural models and reliability using Markov chain Monte Carlo simulation,” Journal of Engineering Mechanics, vol. 128, no. 4, pp. 380–391, 2002. View at Publisher · View at Google Scholar · View at Scopus
  8. O. Basir and X. Yuan, “Engine fault diagnosis based on multi-sensor information fusion using Dempster-Shafer evidence theory,” Information Fusion, vol. 8, no. 4, pp. 379–386, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. Q. G. Fei, A. Q. Li, and X. L. Han, “Simulation study on damage localization of a beam using evidence theory,” Procedia Engineering, vol. 1, no. 1, pp. 147–150, 2009.
  10. A. Smyth and M. Wu, “Multi-rate Kalman filtering for the data fusion of displacement and acceleration response measurements in dynamic system monitoring,” Mechanical Systems and Signal Processing, vol. 21, no. 2, pp. 706–723, 2007. View at Publisher · View at Google Scholar · View at Scopus
  11. T. Boutros and M. Liang, “Mechanical fault detection using fuzzy index fusion,” International Journal of Machine Tools and Manufacture, vol. 47, no. 11, pp. 1702–1714, 2007. View at Publisher · View at Google Scholar · View at Scopus
  12. Y. Y. Liu, Y. F. Ju, C. D. Duan, and X.-F. Zhao, “Structure damage diagnosis using neural network and feature fusion,” Engineering Applications of Artificial Intelligence, vol. 24, no. 1, pp. 87–92, 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. X. Fang, H. Luo, and J. Tang, “Structural damage detection using neural network with learning rate improvement,” Computers and Structures, vol. 83, no. 25-26, pp. 2150–2161, 2005. View at Publisher · View at Google Scholar · View at Scopus
  14. J. Zhang, “Improved on-line process fault diagnosis through information fusion in multiple neural networks,” Computers and Chemical Engineering, vol. 30, no. 3, pp. 558–571, 2006. View at Publisher · View at Google Scholar · View at Scopus
  15. V. N. Vapnik, The Nature of Statistical Learning Theory, Springer Press, 1995.
  16. H. X. He and W. M. Yan, “Structural damage detection with wavelet support vector machine: introduction and applications,” Structural Control and Health Monitoring, vol. 14, no. 1, pp. 162–176, 2007. View at Publisher · View at Google Scholar · View at Scopus
  17. F. M. Reza, An Introduction to Information Theory, Dover Publications, 1994.
  18. C. Wen, Matter-Element Model and Application, Science and Technology Literature Press, 1994.