Smart Structures and Systems

  • 제12권6호
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  • Pages.661-678
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  • 2013
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
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Bridge load testing and rating: a case study through wireless sensing technology

  • Shoukry, Samir N. (Department of Mechanical and Aerospace Eng., West Virginia University) ;
  • Luo, Yan (DEI Group) ;
  • Riad, Mourad Y. (Department of Civil and Environmental Eng., West Virginia University) ;
  • William, Gergis W. (Department of Civil and Environmental Eng., West Virginia University)
  • 투고 : 2012.02.28
  • 심사 : 2013.06.27
  • 발행 : 2013.12.25
⟨ 이전 논문 다음 논문 ⟩

초록

In this paper, a wireless sensing system for structural field evaluation and rating of bridges is presented. The system uses a wireless platform integrated with traditional analogue sensors including strain gages and accelerometers along with the operating software. A wireless vehicle position indicator is developed using a tri-axial accelerometer node that is mounted on the test vehicle, and was used for identifying the moving truck position during load testing. The developed software is capable of calculating the theoretical bridge rating factors based on AASHTO Load and Resistance Factor Rating specifications, and automatically produces the field adjustment factor through load testing data. The sensing system along with its application in bridge deck rating was successfully demonstrated on the Evansville Bridge in West Virginia. A finite element model was conducted for the test bridge, and was used to calculate the load distribution factors of the bridge deck after verifying its results using field data. A confirmation field test was conducted on the same bridge and its results varied by only 3% from the first test. The proposed wireless sensing system proved to be a reliable tool that overcomes multiple drawbacks of conventional wired sensing platforms designed for structural load evaluation of bridges.

키워드

참고문헌

  1. AASHTO Guide Manual for Condition Evaluation and Load and Resistance Factor Rating (LRFR) of Highway Bridges (2003), American association of state highway and transportation officials, Washington,D.C.
  2. Chajes, M.J., Mertz, D.R. and Commander B. (1997), "Experimental load rating of a posted bridge", J. Bridge Eng., 2(1), 1-10. https://doi.org/10.1061/(ASCE)1084-0702(1997)2:1(1)
  3. Chase, S. (2001), "The role of smart structures in managing an aging highway infrastructure", Keynote Presentation in SPIE 8th Annual International Symposium on Smart Structures and Materials, Newport Beach, CA, USA, March 4-8.
  4. Chong, C.Y. and Kumar, S.P. (2003), "Sensor networks: evolution, opportunities, and challenges", P. IEEE, 91(8), 1247-1256. https://doi.org/10.1109/JPROC.2003.814918
  5. Flouri, K., Saukh, O., Sauter, R., Jalsan, K.E., Bischoff, R., Meyer, J. and Feltrin, G. (2012), "A versatile software architecture for civil structure monitoring with wireless sensor networks", Smart Struct. Syst., 10(3), 209-228. https://doi.org/10.12989/sss.2012.10.3.209
  6. Hoover, D.P., Bilbao, A. and Rice, J.A. (2012), "WiSeMote: a novel high fidelity wireless sensor network for structural health monitoring", Smart Struct. Syst., 10(3), 271-298. https://doi.org/10.12989/sss.2012.10.3.271
  7. Kim, J.T., Ho, D.D., Nguyen K.D., Hong D.S., Shin, S.W., Yun, C.B. and Shinozuka, M. (2013), "System identification of a cable-stayed bridge using vibration responses measured by a wireless sensor network", Smart Struct. Syst., 11(5), 533-553. https://doi.org/10.12989/sss.2013.11.5.533
  8. Jo, H., Park, J.W., Spencer, B.F. Jr. and Jung, H.J. (2013), "Develoment of high-sensitivity wireless strain sensor for structural health monitoring" , Smart Struct. Syst., 11 (5), 477-496. https://doi.org/10.12989/sss.2013.11.5.477
  9. Lichtenstein, A.G. (1998), Manual for bridge rating through load testing, Research Results Digest, No. 234, National Cooperative Highway Research Program, Washington, D.C.
  10. Lin, H.R., Chen, C.S., Chen, P.Y., Tsai, F.J., Huang, J.D., Li, J.F., Lin, C.T. and Wu, W.J. (2010), "Design of wireless sensor network and its application for structural health monitoring of cable-stayed bridge", Smart Struct. Syst., 6(8), 939-951. https://doi.org/10.12989/sss.2010.6.8.939
  11. Luo, Y. (2010), "Wireless sensing system for load testing and rating of highway bridges", Ph.D. Dissertation, Department of Mechanical and Aerospace, West Virginia University, Morgantown, WV.
  12. Lynch, J.P. and Loh, K.J. (2006), "A summary review of wireless sensors and sensor networks for structural health monitoring", Shock Vib., 38(2), 91-128. https://doi.org/10.1177/0583102406061499
  13. Ni, Y.Q., Li, B., Lam, K.H., Zhu, D.P., Wang, Y., Lynch, J.P. and Law, K.H. (2011), "In-construction vibration monitoring of a super-tall structure using a long-range wireless sensing system", Smart Struct. Syst., 7(2), 83-102. https://doi.org/10.12989/sss.2011.7.2.083
  14. Phares, B.M., Wipf T.J., Klaber, F.W., Abu-Hawash, A. and Neubauer, S.(2005), "Implementation of physical testing for typical bridge load and superload rating", Transportation Research Record: Journal of the Transportation Research Board (CD-11S): pp. 159-167.
  15. Phares, B.M., Wipf, T.J., Klaber, F.W. and Abu-Hawash, A. (2003), "Bridge load rating using physical testing", Proceedings of the 2003 Mid-Continent Transportation Research Symposium, Ames, Iowa, August 2003.
  16. Selesnick, I.W. (2004), "The double density dual-tree discrete wavelet transforms", IEEE T. Signal Proces., 52 (5).
  17. Straser, E.G. and Kiremidjian, A.S. (1998), A modular, wireless damage monitoring system for structures, Report No. 128, John A. Blume Earthquake Eng. Ctr., Stanford University, Stanford, CA.
  18. Yuan, S., Wang, Z., Qiu, L., Wang, Y. and Liu, M. (2013), "A multi-radio sink node designed for wireless SHM applications", Smart Struct. Syst., 11(3), 261-282. https://doi.org/10.12989/sss.2013.11.3.261
  19. Washer, G. and Fuchs, P. (1998), "Better load ratings through nondestructive evaluation", Public Roads, 62(3), 41-44.

피인용 문헌

  1. Decentralized System Identification Using Stochastic Subspace Identification for Wireless Sensor Networks vol.15, pp.12, 2015, https://doi.org/10.3390/s150408131