Journal of the Korean Society for Nondestructive Testing (비파괴검사학회지)

The Korean Society for Nondestructive Testing (한국비파괴검사학회)
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Bridge Health Monitoring with Consideration of Environmental Effects

  • Received : 2012.10.25
  • Accepted : 2012.12.10
  • Published : 2012.12.30
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Abstract

Reliable response measurements are extremely important for proper bridge health monitoring but incomplete and unreliable data may be acquired due to sensor problems and environmental effects. In the case of a sensor malfunction, parts of the measured data can be missing so that the structural health condition cannot be monitored reliably. This means that the dynamic characteristics of natural frequencies can change as if the structure is damaged due to environmental effects, such as temperature variations. To overcome these problems, this paper proposes a systematic procedure of data analysis to recover missing data and eliminate the environmental effects from the measured data. It also proposes a health index calculated statistically using revised data to evaluate the health condition of a bridge. The proposed method was examined using numerically simulated data with a truss structure and then applied to a set of field data measured from a cable-stayed bridge.

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References

  1. E. Aktan, F. N. Catbas, K. A. Grimmelsman and M. Pervizpour, "Development of a model health monitoring guide for major bridges," Drexel Intelligent Infrastructure and Transportation Safety Institute, pp. 183-230 (2003)
  2. ASME, Power Piping, ASME, B31.1 (1995)
  3. A. Bellino, A. Fasana, L. Garibaldi and S. Marchesiello, "PCA-based detection of damage in time-varying systems," Mechanical Systems and Signal Processing, Vol. 24, pp. 2250-2260 (2010) https://doi.org/10.1016/j.ymssp.2010.04.009
  4. H. Cho, Y. Choi, S. Lee and K. Lee, "Structural damage assessment based on model updating and neural networks," Structure Maintenance and Inspection, Vol. 7-4, pp. 121-128 (2003)
  5. A. Deraemaeker, E. Reynders, G. De. Roeck and J. Kullaa, "Vibration-based structural health monitoring using output-only measurements under changing environment," Mechanical Systems and Signal Processing, Vol. 22, pp. 34-56 (2008) https://doi.org/10.1016/j.ymssp.2007.07.004
  6. J. M. Ko, K. K. Chak, J. Y. Wang, Y. Q. Ni and T.H.T. Chan, "Formulation of an uncertainty model relating modal parameters and environmental factors by using long-term monitoring data," Proceedings Smart Structures and Materials : Smart Systems and Nondestructive Evaluation for Civil Infrastructures 5057, 298-307 (2003)
  7. J. Kullaa, "Damage detection the Z24 bridge using control charts," Mechanical Systems and Signal Processing, Vol. 17(1), pp. 163-170 (2003) https://doi.org/10.1006/mssp.2002.1555
  8. J. Kullaa, "Damage detection under a varying environment using the missing data concept," Proceedings of the 5th International Workshop on Structural Health Monitoring, Stanford, CA. September 12-14, Stanford University, DEStech Publications, pp. 565-573 (2005)
  9. J. Kullaa, "Eliminating environmental or operational influences in structural health monitoring using the missing data analysis," Journal of Intelligent Material Systems and Structures, Vol. 20, pp. 1381-1390 (2009) https://doi.org/10.1177/1045389X08096050
  10. LANDSCOPE, http://www.landmark.re.kr.
  11. H. Li, S. Li, J. Ou and H. Li, "Modal identification of bridges under varying environmental conditions: Temperature and wind effects," Structural Control and Health Monitoring, Wiley InterScience (2009)
  12. G. Manson, S. G. Pierce and K. Worden, "On the long-term stability of normal condition for damage detection in a composite panel," Key Engineering Materials, Vol. 204-205, pp. 359-370 (2001) https://doi.org/10.4028/www.scientific.net/KEM.204-205.359
  13. D. C. Montgomery, "Statistical Quality Control," WILEY (2009)
  14. M. Mehrjoo, N. Khaji, H. Moharrami and A. Bahreininejad, "Damage detection of truss bridge joints using artificial neural networks," Expert Systems with Applications, Vol. 35, pp. 1121-1131 (2008)
  15. Y. Q. Ni, H. F. Zhou and J. M. Ko, "Correlating modal properties with temperature using long-term monitoring data and support vector machine technique," Engineering Structures, Vol. 27, pp. 1762-1773 (2005) https://doi.org/10.1016/j.engstruct.2005.02.020
  16. Y. Q. Ni, H. F. Zhou and J. M. Ko, "Generalization capability of neural network models for temperature-frequency correlation using monitoring data," Journal of Structural Engineering, Vol. 135(10), pp. 1290-1300 (2009) https://doi.org/10.1061/(ASCE)ST.1943-541X.0000050
  17. B. Peeters and G. De Roeck, "One year monitoring of the Z24 bridge: Environmental influences versus damage effects," In Proc. IMAC-XVIII, San Antonio, TX, pp. 1570-1576 (2000)
  18. D. Posenato, P. Kripakaran, D. Inaudi and Ian F. C. Smith, "Methodologies for model-free data interpretation of civil engineering structures," Computers and Structures, Vol. 88, pp. 467-482 (2010) https://doi.org/10.1016/j.compstruc.2010.01.001
  19. R. Ruotolo. "Using SVD to detect damage in structures with different operational condition," Journal of Sound and Vibration, Vol. 2206(3), pp. 425-439 (1999)
  20. N. H. M. K. Serker, Z. S. Wu and S. Z. Li, "A Nonphysics-based approach for vibration-based structural health monitoring under changing environmental conditions," Structural Health Monitoring, Vol. 9(2), pp. 145-158 (2009)
  21. H. Sohn, "Effects of environmental and operational variability on structural health monitoring," Special Issue of Philosophical Transactions of the Royal Society, Structural Health Monitoring, Vol. 365, pp. 539-560 (2007)
  22. S. Vanlanduit, E. Parloo, B. Guillaume, P. Cauberghe and P. Verboven, "A robust singular value decomposition for damage detection under changing operating conditions and structural uncertainties," Journal of Sound and Vibration, Vol. 284, pp. 1033-1050 (2005) https://doi.org/10.1016/j.jsv.2004.07.016
  23. H. Wenzel, "Health Monitoring of Bridges," WILEY, pp. 1-17 (2009)
  24. Z. D. Xu and Z. S. Wu, "Simulation of the efect of temperature variation on damage detection in a long-span cabletayed bridge," Structural Health Monitoring, Vol. 6, pp. 177-189 (2007) https://doi.org/10.1177/1475921707081107
  25. A. M. Yan, G. Kerschen, P. De Boe and J.-C. Golinval, "Structural damage diagnosis under varying environmental conditions - part I: A nonlinear analysis," Mechanical Systems and Signal Processing, Vol. 19(4), pp. 847-864 (2005) https://doi.org/10.1016/j.ymssp.2004.12.002
  26. H. F. Zhou, Y. Q. Ni and J. M. Ko, "Constructing input to neural networks for modeling temperature-cause modal variability: Mean temperatures, effective temperatures, and principal components of temperatures," Engineering Structures, Vol. 32, pp. 1747-1759 (2010) https://doi.org/10.1016/j.engstruct.2010.02.026
  27. Y. Zhu, Y. Fu, W. Chen and S. Huang, "Online deflection monitoring system for Dafosi cable-stayed bridge," Journal of Intelligent Material Systems and Structures, Vol. 17, pp. 701-707 (2006) https://doi.org/10.1177/1045389X06055826