DOI QR코드

DOI QR Code

Strain-based structural condition assessment of an instrumented arch bridge using FBG monitoring data

  • Ye, X.W. (Department of Civil Engineering, Zhejiang University) ;
  • Yi, Ting-Hua (School of Civil Engineering, Dalian University of Technology) ;
  • Su, Y.H. (Department of Civil Engineering, Zhejiang University) ;
  • Liu, T. (Department of Civil Engineering, Zhejiang University) ;
  • Chen, B. (Department of Civil Engineering, Zhejiang University)
  • Received : 2016.12.29
  • Accepted : 2017.04.14
  • Published : 2017.08.25

Abstract

The structural strain plays a significant role in structural condition assessment of in-service bridges in terms of structural bearing capacity, structural reliability level and entire safety redundancy. Therefore, it has been one of the most important parameters concerned by researchers and engineers engaged in structural health monitoring (SHM) practices. In this paper, an SHM system instrumented on the Jiubao Bridge located in Hangzhou, China is firstly introduced. This system involves nine subsystems and has been continuously operated for five years since 2012. As part of the SHM system, a total of 166 fiber Bragg grating (FBG) strain sensors are installed on the bridge to measure the dynamic strain responses of key structural components. Based on the strain monitoring data acquired in recent two years, the strain-based structural condition assessment of the Jiubao Bridge is carried out. The wavelet multi-resolution algorithm is applied to separate the temperature effect from the raw strain data. The obtained strain data under the normal traffic and wind condition and under the typhoon condition are examined for structural safety evaluation. The structural condition rating of the bridge in accordance with the AASHTO specification for condition evaluation and load and resistance factor rating of highway bridges is performed by use of the processed strain data in combination with finite element analysis. The analysis framework presented in this study can be used as a reference for facilitating the assessment, inspection and maintenance activities of in-service bridges instrumented with long-term SHM system.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China, Central Universities of China

References

  1. AASHTO (2011), The Manual for Bridge Evaluation, the 2nd edition. American Association of State Highway and Transportation Officials, Washington DC, USA.
  2. Barbosa, C., Costa, N., Ferreira, L.A., Araujo, F.M., Varum, H., Costa, A., Fernandes, C. and Rodrigues, H. (2008), "Weldable fibre Bragg grating sensors for steel bridge monitoring", Meas. Sci. Technol., 19(12), 125305. https://doi.org/10.1088/0957-0233/19/12/125305
  3. Cardini, A.J. and DeWolf, J.T. (2008), "Long-term structural health monitoring of a multi-girder steel composite bridge using strain data", Struct. Health Monit., 8(1), 47-58. https://doi.org/10.1177/1475921708094789
  4. Casas, J.R. and Cruz, P.J.S. (2003), "Fiber optic sensors for bridge monitoring", J. Bridge Eng. - ASCE, 8(6), 362-373. https://doi.org/10.1061/(ASCE)1084-0702(2003)8:6(362)
  5. Chan, T.H.T., Yu, L., Tam, H.Y., Ni, Y.Q., Liu, S.Y., Chung, W.H. and Cheng, L.K. (2006), "Fiber Bragg grating sensors for structural health monitoring of Tsing Ma bridge: background and experimental observation", Eng. Struct., 28, 648-659. https://doi.org/10.1016/j.engstruct.2005.09.018
  6. Costa, B.J.A. and Figueiras, J.A. (2012), "Fiber optical based monitoring system applied to a centenary metallic arch bridge: design and installation", Eng. Struct., 44, 271-280. https://doi.org/10.1016/j.engstruct.2012.06.005
  7. Fuhr, P.L., Huston, D.R., Nelson, M., Nelson, O., Hu, J. and Mowat, E. (1999), "Fiber optic sensing of a bridge in Waterbury, Vermont", J. Intel. Mat. Syst. Str., 10(4), 293-303. https://doi.org/10.1177/1045389X9901000405
  8. Hill, K.O., Fujii, Y., Johnson, D.C. and Kawasaki, B.S. (1978). "Photosensitivity in optical fiber waveguides: Application to reflection filter fabrication", Appl. Phys. Lett., 32(10), 647-649. https://doi.org/10.1063/1.89881
  9. Jiang, G.L., Dawood, M., Peters, K. and Rizkalla, S. (2010), "Global and local fiber optic sensors for health monitoring of civil engineering infrastructure retrofit with FRP materials", Struct. Health Monit., 9(4), 309-322. https://doi.org/10.1177/1475921709352989
  10. Kister, G., Badcock, R.A., Gebremichael, Y.M., Boyle, W.J.O., Grattan, K.T.V., Fernando, G.F. and Canning, L. (2007a), "Monitoring of an all-composite bridge using Bragg grating sensors", Constr. Build. Mater., 21(7), 1599-1604. https://doi.org/10.1016/j.conbuildmat.2006.07.007
  11. Kister, G., Winter, D., Badcock, R.A., Gebremichael, Y.M., Boyle, W.J.O., Meggitt, B.T., Grattan, K.T.V. and Fernando, G.F. (2007b), "Structural health monitoring of a composite bridge using Bragg grating sensors. Part 1: evaluation of adhesives and protection systems for the optical sensors", Eng. Struct., 29(3), 440-448. https://doi.org/10.1016/j.engstruct.2006.05.012
  12. Li, H., Ou, J.P., Zhao, X.F., Zhou, W.S., Li, H.W. and Zhou, Z. (2006), "Structural health monitoring system for the Shandong Binzhou Yellow River Highway Bridge", Comput.-Aided Civ. Inf., 21(4), 306-317. https://doi.org/10.1111/j.1467-8667.2006.00437.x
  13. Mehrani, E., Ayoub, A. and Ayoub, A. (2009), "Evaluation of fiber optic sensors for remote health monitoring of bridge structures", Mater. Struct., 42(2), 183-199. https://doi.org/10.1617/s11527-008-9377-7
  14. Ni, Y.Q., Ye, X.W. and Ko, J.M. (2010), "Monitoring-based fatigue reliability assessment of steel bridges: analytical model and application", J. Struct. Eng. - ASCE, 136(12), 1563-1573. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000250
  15. Ni, Y.Q., Xia, H.W., Wong, K.Y. and Ko, J.M. (2012a), "In-service condition assessment of bridge deck using long-term monitoring data of strain response", J. Bridge Eng. - ASCE, 17(6), 876-885. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000321
  16. Ni, Y.Q., Ye, X.W. and Ko, J.M. (2012b), "Modeling of stress spectrum using long-term monitoring data and finite mixture distributions", J. Eng. Mech. - ASCE, 138(2), 175-183. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000313
  17. Rodrigues, C., Cavadas, F., Felix, C. and Figueiras, J. (2012), "FBG based strain monitoring in the rehabilitation of a centenary metallic bridge", Eng. Struct., 44, 281-290. https://doi.org/10.1016/j.engstruct.2012.05.040
  18. Surre, F., Sun, T. and Grattan, K.T. (2013), "Fiber optic strain monitoring for long-term evaluation of a concrete footbridge under extended test conditions", IEEE Sens. J., 13(3), 1036-1043. https://doi.org/10.1109/JSEN.2012.2234736
  19. Tennyson, R.C., Mufti, A.A., Rizkalla, S., Tadros, G. and Benmokrane, B. (2001), "Structural health monitoring of innovative bridges in Canada with fiber optic sensors", Smart. Mater. Struct., 10(3), 560-573. https://doi.org/10.1088/0964-1726/10/3/320
  20. Xia, H.W., Ni, Y.Q., Wong, K.Y. and Ko, J.M. (2012), "Reliability-based condition assessment of in-service bridges using mixture distribution models", Comput. Struct., 106-107, 204-213. https://doi.org/10.1016/j.compstruc.2012.05.003
  21. Xiong, W., Cai, C.S. and Kong, X. (2012), "Instrumentation design for bridge scour monitoring using fiber Bragg grating sensors", Appl. Optics, 51(5), 547-557. https://doi.org/10.1364/AO.51.000547
  22. Ye, X.W., Ni, Y.Q., Wong, K.Y. and Ko, J.M. (2012), "Statistical analysis of stress spectra for fatigue life assessment of steel bridges with structural health monitoring data", Eng. Struct., 45, 166-176. https://doi.org/10.1016/j.engstruct.2012.06.016
  23. Ye, X.W., Ni, Y.Q., Wai, T.T., Wong, K.Y., Zhang, X.M. and Xu, F. (2013), "A vision-based system for dynamic displacement measurement of long-span bridges: algorithm and verification", Smart Struct. Syst., 12(3-4), 363-379. https://doi.org/10.12989/sss.2013.12.3_4.363
  24. Ye, X.W., Su, Y.H. and Han, J.P. (2014), "Structural health monitoring of civil infrastructure using optical fiber sensing technology: A comprehensive review", Sci. World J., 2014, Article ID 652329, 1-11.
  25. Ye, X.W., Dong, C.Z. and Liu, T. (2016a), "Image-based structural dynamic displacement measurement using different multi-object tracking algorithms", Smart Struct. Syst., 17(6), 935-956. https://doi.org/10.12989/sss.2016.17.6.935
  26. Ye, X.W., Su, Y.H., Xi, P.S., Chen, B. and Han, J.P. (2016b), "Statistical analysis and probabilistic modeling of WIM monitoring data of an instrumented arch bridge", Smart Struct. Syst., 17(6), 1087-1105. https://doi.org/10.12989/sss.2016.17.6.1087
  27. Ye, X.W., Dong, C.Z. and Liu, T. (2016c), "Force monitoring of steel cables using vision-based sensing technology: methodology and experimental verification", Smart Struct. Syst., 18(3), 585-599. https://doi.org/10.12989/sss.2016.18.3.585
  28. Ye, X.W., Liu, T. and Ni, Y.Q. (2017), "Probabilistic corrosion fatigue life assessment of a suspension bridge instrumented with long-term SHM system", Adv. Struct. Eng., DOI: 10.1177/1369433217698345.
  29. Zhang, W., Gao, J.Q., Shi, B., Cui, H.L. and Zhu, H.H. (2006), "Health monitoring of rehabilitated concrete bridges using distributed optical fiber sensing", Comput.-Aided Civ. Inf., 21(6), 411-424. https://doi.org/10.1111/j.1467-8667.2006.00446.x
  30. Zhou, G.D., Yi, T.H. and Chen, B. (2016), "Innovative design of a health monitoring system and its implementation in a complicated long-span arch bridge", J. Aerospace Eng. - ASCE, B4016006, 1-17.

Cited by

  1. A novel OFDR-based distributed optical fiber sensing tape: design, optimization, calibration and application vol.29, pp.10, 2017, https://doi.org/10.1088/1361-665x/ab939a