Computers and Concrete

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

A systematic method from influence line identification to damage detection: Application to RC bridges

  • Chen, Zhiwei (Department of Civil Engineering, Xiamen University) ;
  • Yang, Weibiao (Department of Civil Engineering, Xiamen University) ;
  • Li, Jun (Centre for Infrastructural Monitoring and Protection, School of Civil and Mechanical Engineering, Curtin University) ;
  • Cheng, Qifeng (Holsin Engineering Testing Co., LTD) ;
  • Cai, Qinlin (Department of Civil Engineering, Xiamen University)
  • Received : 2017.07.25
  • Accepted : 2017.08.19
  • Published : 2017.11.25
⟨ Previous Next ⟩

Abstract

Ordinary reinforced concrete (RC) and prestressed concrete bridges are two popular and typical types of short- and medium-span bridges that accounts for the vast majority of all existing bridges. The cost of maintaining, repairing or replacing degraded existing RC bridges is immense. Detecting the abnormality of RC bridges at an early stage and taking the protective measures in advance are effective ways to improve maintenance practices and reduce the maintenance cost. This study proposes a systematic method from influence line (IL) identification to damage detection with applications to RC bridges. An IL identification method which integrates the cubic B-spline function with Tikhonov regularization is first proposed based on the vehicle information and the corresponding moving vehicle induced bridge response time history. Subsequently, IL change is defined as a damage index for bridge damage detection, and information fusion technique that synthesizes ILs of multiple locations/sensors is used to improve the efficiency and accuracy of damage localization. Finally, the feasibility of the proposed systematic method is verified through experimental tests on a three-span continuous RC beam. The comparison suggests that the identified ILs can well match with the baseline ILs, and it demonstrates that the proposed IL identification method has a high accuracy and a great potential in engineering applications. Results in this case indicate that deflection ILs are superior than strain ILs for damage detection of RC beams, and the performance of damage localization can be significantly improved with the information fusion of multiple ILs.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China

References

  1. AASHTO (2010), AASHTO LRFD Bridge Design Specifications, 5th Edition, Washington, U.S.A.
  2. AASHTO (2011), The Manual for Bridge Evaluation, 2nd Edition, American Association of State Highway and Transportation Officials Subcommittee on Bridges Structures, Washington, U.S.A.
  3. Aktan, A.E. and Catbas, F.N. (2002), "Condition and damage assessment: Issues and some promising indices", J. Struct. Eng., 128(8), 1026-1036. https://doi.org/10.1061/(ASCE)0733-9445(2002)128:8(1026)
  4. Basir, O. and Yuan, X.H. (2007), "Engine fault diagnosis based on multi-sensor information fusion using dempster-shafer evidence theory", Informat. Fus., 8(4), 379-386. https://doi.org/10.1016/j.inffus.2005.07.003
  5. Chen, B. and Xu, Y.L. (2007), "A new damage index for detecting sudden change of structural stiffness", J. Struct. Eng. Mech., 26(3), 315-341. https://doi.org/10.12989/sem.2007.26.3.315
  6. Chen, Z.W., Xu, Y.L. and Wang, X.M. (2012), "SHMS-based fatigue reliability analysis of multi-loading suspension bridges", J. Struct. Eng., 138(3), 299-307. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000460
  7. Chen, Z.W., Zhu, S.Y., Xu, Y.L., Li, Q. and Cai, Q.L. (2015), "Damage detection in long suspension bridges using stress influence lines", J. Brid. Eng., 20(3), 05014013. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000681
  8. Choi, I.Y., Lee, S.J., Choi, E. and Cho, H.N. (2004), "Development of elastic damage load theorem for damage detection in a statically determine beam", Comput. Struct., 82(29-30), 2483-2492. https://doi.org/10.1016/j.compstruc.2004.07.003
  9. Ding, Y.L., Song, Y.S., Cao, B.Y., Wang, G.X. and Li, A.Q. (2016), "Full-range S-N fatigue-life evaluation method for welded bridge structures considering hot-spot and welding residual stress", J. Brid. Eng., 21(12), 04016096. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000969
  10. Ding, Y.L., Zhao, H.W. and Li, A.Q. (2017), "Temperature effects on strain influence lines and dynamic load factors in a steeltruss arch railway bridge using adaptive FIR filtering", J. Perform. Constr. Facilit., 1943-5509.0001026.
  11. Doebling, S.W., Farrar, C.R. and Prime, M.B. (1998), "A summary review of vibration-based damage identification methods", Shock Vibr. Dig., 30(2), 91-105. https://doi.org/10.1177/058310249803000201
  12. Fan, W. and Qiao, P. (2011), "Vibration-based damage identification methods: A review and comparative study", Struct. Health Monitor., 10(1), 83-111. https://doi.org/10.1177/1475921710365419
  13. Fang, S.E. and Perera, R. (2009), "Power mode shapes for early damage detection in linear structures", J. Sound Vibr., 324(1-2), 40-56. https://doi.org/10.1016/j.jsv.2009.02.002
  14. Fang, S.E., Perera, R. and Roeck, G.D. (2008), "Damage identification of a reinforced concrete frame by finite element model updating using damage parameterization", J. Sound Vibr., 313(3-5), 544-559. https://doi.org/10.1016/j.jsv.2007.11.057
  15. Hansen, P.C. (1992), "Analysis of discrete ill-posed problems by means of the L-curve", SIAM Rev., 34(4), 561-580. https://doi.org/10.1137/1034115
  16. Hibbeler, R.C. (2009), Structural Analysis, Pearson Prentice Hall, Singapore.
  17. Judd, K.L. (1998), Numerical Methods in Economics, MIT Press.
  18. Li, H.N., Yi, T.H., Ren, L., Li, D.S. and Huo, L.S. (2014), "Reviews on innovations and applications in structural health monitoring for infrastructures", Struct. Monitor. Mainten., 1(1), 1-45. https://doi.org/10.12989/smm.2014.1.1.001
  19. Li, J. and Hao, H. (2014), "Substructure damage identification based on wavelet domain response reconstruction", Struct. Health Monitor., 13(4), 389-405. https://doi.org/10.1177/1475921714532991
  20. Li, J. and Hao, H. (2016), "A review of recent research advances on structural health monitoring in Western Australia", Struct. Monitor. Mainten., 3(1), 33-49. https://doi.org/10.12989/smm.2016.3.1.033
  21. McCann, D.M. and Forde, M.C. (2001), "Review of NDT methods in the assessment of concrete and masonry structures", NDT E Int., 34(2), 71-84. https://doi.org/10.1016/S0963-8695(00)00032-3
  22. Stewart, M.G. and Mullard, J.A. (2007), "Spatial time-dependent reliability analysis of corrosion damage and the timing of first repair for RC structures", Eng. Struct., 29(7), 1457-1464. https://doi.org/10.1016/j.engstruct.2006.09.004
  23. Sun, S.W., Sun, L.M. and Chen, L. (2015), "Damage detection based on structural response induced by traffic load: Methodology and application", J. Struct. Stab. Dyn., 16(4), 1640026.
  24. Vogel, C.R. (2002), Computational Methods for Inverse Problems, Society for Industrial and Applied Mathematics, Philadelphia, U.S.A.
  25. Vu, K. and Stewart, M.G. (2000), "Structural reliability of concrete bridges including improved chloride-induced corrosion models", Struct. Safety, 22(4), 313-333. https://doi.org/10.1016/S0167-4730(00)00018-7
  26. Yan, W.J., Ren, W.X. and Huang, T.L. (2012), "Statistic structural damage detection based on the closed-form of element modal strain energy sensitivity", Mech. Syst. Sign. Proc., 28(2), 183-194. https://doi.org/10.1016/j.ymssp.2011.04.011
  27. Yi, T.H., Li, H.N. and Gu, M. (2011), "Characterization and extraction of global positioning system multipath signals using an improved particle-filtering algorithm", Measure. Sci. Technol., 22(7), 075101. https://doi.org/10.1088/0957-0233/22/7/075101
  28. Yi, T.H., Li, H.N. and Gu, M. (2013b), "Experimental assessment of high-rate GPS receivers for deformation monitoring of bridge", Measure., 46(1), 420-432.
  29. Yi, T.H., Li, H.N. and Sun, H.M. (2013a), "Multi-stage structural damage diagnosis method based on 'energy-damage' theory", Smart Struct. Syst., 12(3-4), 345-361. https://doi.org/10.12989/sss.2013.12.3_4.345
  30. Zaurin, R. and Catbas, F.N. (2011), "Structural health monitoring using video stream, influence lines, and statistical analysis", Struct. Health Monitor., 10(3), 309-332. https://doi.org/10.1177/1475921710373290
  31. Zaurin, R., Khuc, T. and Catbas, F.N. (2016), "Hybrid sensorcamera monitoring for damage detection: Case study of a real bridge", J. Brid. Eng., 21(6), 05016002. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000811

Cited by

  1. Design and application of structural health monitoring system in long-span cable-membrane structure vol.18, pp.2, 2019, https://doi.org/10.1007/s11803-019-0484-y