Structural Monitoring and Maintenance

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Condition monitoring and rating of bridge components in a rail or road network by using SHM systems within SRP

  • Aflatooni, Mehran (School of Civil Engineering and Built Environment, Science and Engineering Faculty, Queensland University of Technology) ;
  • Chan, Tommy H.T (School of Civil Engineering and Built Environment, Science and Engineering Faculty, Queensland University of Technology) ;
  • Thambiratnam, David P. (School of Civil Engineering and Built Environment, Science and Engineering Faculty, Queensland University of Technology)
  • Received : 2015.03.12
  • Accepted : 2015.08.17
  • Published : 2015.09.25
⟨ Previous Next ⟩

Abstract

The safety and performance of bridges could be monitored and evaluated by Structural Health Monitoring (SHM) systems. These systems try to identify and locate the damages in a structure and estimate their severities. Current SHM systems are applied to a single bridge, and they have not been used to monitor the structural condition of a network of bridges. This paper propose a new method which will be used in Synthetic Rating Procedures (SRP) developed by the authors of this paper and utilizes SHM systems for monitoring and evaluating the condition of a network of bridges. Synthetic rating procedures are used to assess the condition of a network of bridges and identify their ratings. As an additional part of the SRP, the method proposed in this paper can continuously monitor the behaviour of a network of bridges and therefore it can assist to prevent the sudden collapses of bridges or the disruptions to their serviceability. The method could be an important part of a bridge management system (BMS) for managers and engineers who work on condition assessment of a network of bridges.

Keywords

Acknowledgement

Grant : Life Cycle Management of Railway Bridges

References

  1. Abdalla, M., Grigoriadis, K. and Zimmerman, D. (2000), "Structural damage detection using linear matrix inequality methods", J. Vib. Acoust., 122(4), 448-455. https://doi.org/10.1115/1.1287029
  2. Aflatooni, M. (2015), Synthetic Rating System for Railway Bridge Management, PhD Thesis, Queensland University of Technology.
  3. Aflatooni, M., Chan, T.H.T. and Thambiratnam, D.P. (2014), "Synthetic rating procedures for rating railway bridges", J. Bridge Eng., 19(12), doi: 10.1061/(ASCE)BE.1943-5592.0000623
  4. Aflatooni, M., Chan, T.H.T. and Thambiratnam, D.P. (2015), "A new look at the restrictions on the speed and magnitude of train loads for bridge management", Struct. Eng. Mech., 53(1), 89-104. https://doi.org/10.12989/sem.2015.53.1.089
  5. Bandara, A.R.P. (2013), Damage identification and condition assessment of building structures using frequency response functions and neural networks.
  6. Bandara, R.P., Chan, T.H. and Thambiratnam, D.P. (2014), "Frequency response function based damage identification using principal component analysis and pattern recognition technique", Eng. Struct., 66, 116-128. https://doi.org/10.1016/j.engstruct.2014.01.044
  7. Bao, X., DeMerchant, M., Brown, A. and Bremner, T. (2001), "Tensile and compressive strain measurement in the lab and field with the distributed Brillouin scattering sensor", J. Lightwave Technol., 19(11), 1698. https://doi.org/10.1109/50.964070
  8. Catbas, F., Gul, M. and Burkett, J. (2008), "Damage assessment using flexibility and flexibility-based curvature for structural health monitoring", Smart Mater. Struct., 17(1), 015024. https://doi.org/10.1088/0964-1726/17/01/015024
  9. Chan, T.H., Ashebo, D.B., Tam, H., Yu, Y., Chan, T., Lee, P. and Gracia, E.P. (2009), "Vertical displacement measurements for bridges using optical fiber sensors and CCD cameras-a preliminary study", Struct. Health Monit., 8(3), 243-249. https://doi.org/10.1177/1475921708102108
  10. Chan, T.H. and Wang, Y. (2013), "Australian network of structural health monitoring", Australian J. Struct. Eng., 14(1).
  11. Chan, T.H., Yu, L., Tam, H.Y., Ni, Y.Q., Liu, S., Chung, W. and Cheng, L. (2006), "Fiber bragg grating sensors for structural health monitoring of Tsing Ma bridge: Background and experimental observation", Eng. Struct., 28(5), 648-659. https://doi.org/10.1016/j.engstruct.2005.09.018
  12. Chan, T.H.T. and Thambiratnam, D.P. (2011), Structural Health Monitoring in Australia. Brisbane, Australia: Nova Science Publishers, Hauppauge NY.
  13. Chan, T.H.T., Wong, K., Li, Z. and Ni, Y.Q. (2011), Structural health monitoring for long span bridges: Hong Kong experience & continuing onto Australia, Chapter 1 in Structural Health Monitoring in Australia, edited by Chan, T.H.T and Thambiratnam, D.P.: NOVA Science Publishers, Inc.
  14. Hassiotis, S. (2000), "Identification of damage using natural frequencies and Markov parameters", Comput. Struct., 74(3), 365-373. https://doi.org/10.1016/S0045-7949(99)00034-6
  15. Henault, J.M., Quiertant, M., Delepine-Lesoille, S., Salin, J., Moreau, G., Taillade, F. and Benzarti, K. (2012), "Quantitative strain measurement and crack detection in RC structures using a truly distributed fiber optic sensing system", Constr. Build. Mater., 37, 916-923. https://doi.org/10.1016/j.conbuildmat.2012.05.029
  16. Jauregui, D.V., White, K.R., Woodward, C.B. and Leitch, K.R. (2003), "Noncontact photogrammetric measurement of vertical bridge deflection", J. Bridge Eng., 8(4), 212-222. https://doi.org/10.1061/(ASCE)1084-0702(2003)8:4(212)
  17. Ko, J. and Ni, Y. (2005), "Technology developments in structural health monitoring of large-scale bridges", Eng. Structu., 27(12), 1715-1725. https://doi.org/10.1016/j.engstruct.2005.02.021
  18. Lee, J.J., Lee, J.W., Yi, J.H., Yun, C.B. and Jung, H.Y. (2005), "Neural networks-based damage detection for bridges considering errors in baseline finite element models", J. Sound Vib., 280(3), 555-578. https://doi.org/10.1016/j.jsv.2004.01.003
  19. Li, Z., Chan, T.H. and Zheng, R. (2003), "Statistical analysis of online strain response and its application in fatigue assessment of a long-span steel bridge", Eng. Struct., 25(14), 1731-1741. https://doi.org/10.1016/S0141-0296(03)00174-3
  20. Li, Z. and Chan, T.H.T. (2006), "Fatigue criteria for integrity assessment of long-span steel bridge with health monitoring", Theor. Appl. Fract. Mech., 46(2), 114-127. https://doi.org/10.1016/j.tafmec.2006.07.003
  21. Li, Z., Chan, T.H.T., Yu, Y. and Sun, Z. (2009), "Concurrent multi-scale modeling of civil infrastructures for analyses on structural deterioration--Part I: Modeling methodology and strategy", Finite Elem. Anal. Des., 45(11), 782-794. https://doi.org/10.1016/j.finel.2009.06.013
  22. Liang, M.T., Wu, J.H. and Liang, C.H. (2001), "Multiple layer fuzzy evaluation for existing reinforced concrete bridges", J. Infrastruct. Syst., 7(4), 144. https://doi.org/10.1061/(ASCE)1076-0342(2001)7:4(144)
  23. Micro measurements a VPG Brand. (2014), Strain Gauge Selection: Criteria, Procedures, Recommendations Retrieved 19/11/2014, 2014, from http://www.vishaypg.com/docs/11055/tn505.pdf
  24. Nobahari, M. and Seyedpoor, S. (2011), "Structural damage detection using an efficient correlation-based index and a modified genetic algorithm", Math. Comput. Modell., 53(9), 1798-1809. https://doi.org/10.1016/j.mcm.2010.12.058
  25. Ogundipe, O., Roberts, G.W. and Brown, C.J. (2014), "GPS monitoring of a steel box girder viaduct", Struct. Infrastruct. E., 10(1), 25-40. https://doi.org/10.1080/15732479.2012.692387
  26. Park, H., Lee, H., Adeli, H. and Lee, I. (2007), "A new approach for health monitoring of structures: terrestrial laser scanning", Comput. Aided Civil Infrastruct. E., 22(1), 19-30. https://doi.org/10.1111/j.1467-8667.2006.00466.x
  27. Radzienski, M., Krawczuk, M. and Palacz, M. (2011), "Improvement of damage detection methods based on experimental modal parameters", Mech. Syst. Signal Pr., 25(6), 2169-2190. https://doi.org/10.1016/j.ymssp.2011.01.007
  28. Reynders, E., Teughels, A. and De Roeck, G. (2010), "Finite element model updating and structural damage identification using OMAX data", Mech. Syst. Signal Pr., 24(5), 1306-1323. https://doi.org/10.1016/j.ymssp.2010.03.014
  29. Roy, K. and Ray-Chaudhuri, S. (2013), "Fundamental mode shape and its derivatives in structural damage localization", J. Sound Vib., 332(21), 5584-5593. https://doi.org/10.1016/j.jsv.2013.05.003
  30. Salawu, O. (1997), "Detection of structural damage through changes in frequency: a review", Eng. Struct., 19(9), 718-723. https://doi.org/10.1016/S0141-0296(96)00149-6
  31. Sampaio, R., Maia, N. and Silva, J. (1999), "Damage detection using the frequency-response-function curvature method", J. Sound Vib., 226(5), 1029-1042. https://doi.org/10.1006/jsvi.1999.2340
  32. Shih, H.W., Thambiratnam, D.P. and Chan, T.H. (2009), "Vibration based structural damage detection in flexural members using multi-criteria approach", J. Sound Vib., 323(3), 645-661. https://doi.org/10.1016/j.jsv.2009.01.019
  33. Sohn, H. (2004), A review of structural health monitoring literature: 1996-2001: Los Alamos National Laboratory.
  34. Taha, M.R., Noureldin, A., Lucero, J. and Baca, T. (2006), "Wavelet transform for structural health monitoring: a compendium of uses and features", Struct. Health Monit., 5(3), 267-295. https://doi.org/10.1177/1475921706067741
  35. Vurpillot, S., Inaudi, D. and Scano, A. (1996), Mathematical model for the determination of the vertical displacement from internal horizontal measurements of a bridge, Paper presented at the 1996 Symposium on Smart Structures and Materials.
  36. Wang, F., Chan, T., Thambiratnam, D. and Tan, A.C. (2013), "A statistical strategy to select optimal structural health monitoring data in operational modal analysis", Australian J. Struct. Eng., 14(1), 1-12.
  37. Wang, L. (2012), Innovative damage assessment of steel truss bridges using modal strain energy correlation, PhD Thesis, Queensland University of Technology.
  38. Wu, J. and Li, Q. (2006), "Structural parameter identification and damage detection for a steel structure using a two-stage finite element model updating method", J. Constr. Steel Res., 62(3), 231-239. https://doi.org/10.1016/j.jcsr.2005.07.003
  39. Yang, J.N. and Lin, S. (2005), "Identification of parametric variations of structures based on least squares estimation and adaptive tracking technique", J. Eng. Mech. -ASCE, 131(3), 290-298. https://doi.org/10.1061/(ASCE)0733-9399(2005)131:3(290)
  40. Yau, M.H. (2014), Vertical displacement measurement using fibre Bragg grating (FBG) sensors for structural health monitoring of bridges.
  41. Yau, M.H., Chan, T.H., Thambiratnam, D. and Tam, H. (2013), "Static vertical displacement measurement of bridges using fiber Bragg grating (FBG) sensors", Adv. Struct. Eng., 16(1), 165-176. https://doi.org/10.1260/1369-4332.16.1.165
  42. Zhou, Y.E. (2006), "Assessment of bridge remaining fatigue life through field strain measurement", J. Bridge Eng., 11(6), 737-744. https://doi.org/10.1061/(ASCE)1084-0702(2006)11:6(737)

Cited by

  1. Influence of bias magnetic field for sleeve eddy current sensor (SECS) in tension measurement vol.263, 2017, https://doi.org/10.1016/j.sna.2017.07.002
  2. Investigation on Eddy Current Sensor in Tension Measurement at a Resonant Frequency vol.7, pp.6, 2017, https://doi.org/10.3390/app7060538
  3. Study on an innovative self-inductance tension eddy current sensor based on the inverse magnetostrictive effect vol.37, pp.1, 2017, https://doi.org/10.1108/SR-08-2016-0145