Smart Structures and Systems

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Multiscale features and information extraction of online strain for long-span bridges

  • Wu, Baijian (Department of Engineering Mechanics, Southeast University) ;
  • Li, Zhaoxia (Department of Engineering Mechanics, Southeast University) ;
  • Chan, Tommy H.T. (School of Civil Engineering and Built Environment, Science and Engineering Faculty, Queensland University of Technology) ;
  • Wang, Ying (Department of Engineering Mechanics, Southeast University)
  • Received : 2013.05.14
  • Accepted : 2014.04.25
  • Published : 2014.10.25
⟨ Previous Next ⟩

Abstract

The strain data acquired from structural health monitoring (SHM) systems play an important role in the state monitoring and damage identification of bridges. Due to the environmental complexity of civil structures, a better understanding of the actual strain data will help filling the gap between theoretical/laboratorial results and practical application. In the study, the multi-scale features of strain response are first revealed after abundant investigations on the actual data from two typical long-span bridges. Results show that, strain types at the three typical temporal scales of $10^5$, $10^2$ and $10^0$ sec are caused by temperature change, trains and heavy trucks, and have their respective cut-off frequency in the order of $10^{-2}$, $10^{-1}$ and $10^0$ Hz. Multi-resolution analysis and wavelet shrinkage are applied for separating and extracting these strain types. During the above process, two methods for determining thresholds are introduced. The excellent ability of wavelet transform on simultaneously time-frequency analysis leads to an effective information extraction. After extraction, the strain data will be compressed at an attractive ratio. This research may contribute to a further understanding of actual strain data of long-span bridges; also, the proposed extracting methodology is applicable on actual SHM systems.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation

References

  1. Bukkapatnam, S.T.S., Nichols, J.M., Seaver, M., Trickey, S.T. and Hunter, M.. (2005), "A wavelet-based, distortion energy approach to structural health monitoring", Structural Health Monit., 4(3), 247-258. https://doi.org/10.1177/1475921705055246
  2. Cardini, A.J. and DeWolf, J.T. (2009), "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
  3. Chan, H.T., Guo, L. and Li, Z.X. (2003), "Finite element modelling for fatigue stress analysis of large suspension bridges", J. Sound Vib., 261(3), 443-464. https://doi.org/10.1016/S0022-460X(02)01086-6
  4. Chan, H.T., Li, Z.X. and Ko, J.M. (2001), "Fatigue analysis and life prediction of bridges with structural health monitoring data-Part II: application", Int. J. Fatigue, 23(1), 55-64.
  5. Chen, S.R. and Wu, J. (2008), "Performance enhancement of bridge infrastructure systems: Long-span bridge, moving trucks and wind with tuned mass dampers", Eng. Struct., 30(11), 3316-3324. https://doi.org/10.1016/j.engstruct.2008.04.035
  6. Daubechies, I. (1992), Ten lectures on wavelets (Vol. 61): SIAM.
  7. Donoho, D.L. and Johnstone, J.M. (1994), "Ideal spatial adaptation by wavelet shrinkage", Biometrika, 81(3), 425-455. https://doi.org/10.1093/biomet/81.3.425
  8. Donoho, D.L. (1995). "De-noising by soft-thresholding". Information Theory, IEEE Transactions on, 41(3), 613-627. https://doi.org/10.1109/18.382009
  9. Farrar, C.R., Sohn, H., Fugate, M.L. and Czarnecki, J.J. (2001), Integrated structural health monitoring, Paper presented at the 6th Annual International Symposium on NDE for Health Monitoring and Diagnostics.
  10. Housner, G.W., Bergman, L.A., Caughey, T.K., Chassiakos, A.G., Claus, R.O., Masri, S.F. and Yao, T.P. (1997), "Structural control: past, present, and future", J. Eng. Mech.-ASCE, 123(9), 897-971. https://doi.org/10.1061/(ASCE)0733-9399(1997)123:9(897)
  11. Hu, X.F. and Shenton H.W. (2007), "Dead load based damage identification method for long-term structural health monitoring", J. Intelligent Mat. Syst. Str., 18(9), 923-938. https://doi.org/10.1177/1045389X06070599
  12. Kamath, G.M., Sundaram, R., Gupta, N. and Rao, M.S. (2010), "Damage studies in composite structures for structural health monitoring using strain sensors", Struct. Health Monit., 9(6), 497-512. https://doi.org/10.1177/1475921710365391
  13. Katsikeros, C.E. and Labeas, G.N. (2009), "Development and validation of a strain-based structural health monitoring system", Mech. Syst. Signal Pr., 23(2), 372-383. https://doi.org/10.1016/j.ymssp.2008.03.006
  14. Kesavan, A., John, S. and Herszberg, I. (2008), "Strain-based structural health monitoring of complex composite structures", Struct. Health Monit., 7(3), 203-213. https://doi.org/10.1177/1475921708090559
  15. Lau, C.K. and Wong, KY. (1997), "Design, construction and monitoring of the three key cable-supported bridges in Hong Kong", Proceedings of the 4th International Kerensky Conference on Structures in the new millennium, Hong Kong.
  16. Li, S.Z. and Wu, Z.S. (2008), "Modal analysis on macro-strain measurements from distributed long-gage fiber optic sensors", J. Intel. Mat. Syst. Str., 19(8), 937-946. https://doi.org/10.1177/1045389X07082477
  17. Li, Y. H., Tang, L.Q., Liu, Z.J. and Liu, Y.P. (2012), "Statistics and probability analysis of vehicle overloads on a rigid frame bridge from long-term monitored strains", Smart Struct. Syst., 9(3), 287-301. https://doi.org/10.12989/sss.2012.9.3.287
  18. Li, Z.X., Chan, H.T. and Ko, J.M. (2001), "Fatigue analysis and life prediction of bridges with structural health monitoring data-Part I: methodology and strategy", Int. J. Fatigue, 23(1), 45-53. https://doi.org/10.1016/S0142-1123(00)00068-2
  19. Li, Z.X., Chan H.T. and Ko, J.M. (2002), "Evaluation of typhoon induced fatigue damage for Tsing Ma Bridge", Eng. Struct., 24(8), 1035-1047. https://doi.org/10.1016/S0141-0296(02)00031-7
  20. Liu, M., Frangopol, D.M. and Kim, S. (2009), "Bridge system performance assessment from structural health monitoring: a case study", J. Struct. Eng.-ASCE, 135(6), 733-742. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000014
  21. Mallat, S.G. (1989), "A theory for multiresolution signal decomposition: the wavelet representation", IEEE T. Pattern Anal., 11(7), 674-693. https://doi.org/10.1109/34.192463
  22. Mallat, S. and Hwang, W.L. (1992), "Singularity detection and processing with wavelets", IEEE T. Inform. Theory, 38(2), 617-643. https://doi.org/10.1109/18.119727
  23. Mitra, S.K. and Kuo, Y.H. (2006), Digital signal processing: a computer-based approach (Vol. 2), McGraw-Hill New York.
  24. Nason, G.P. (1995), "Choice of the threshold parameter in wavelet function estimation", Wavelets Statistics, 261-280.
  25. Omenzetter, P., Brownjohn, J.M.W. and Moyo, P. (2004), "Identification of unusual events in multi-channel bridge monitoring data", Mech. Syst. Signal Pr., 18(2), 409-430. https://doi.org/10.1016/S0888-3270(03)00040-2
  26. Reynders, E., Roeck, G.D., Gundes B.P. and Sauvage, C. (2007), "Damage identification on the Tilff Bridge by vibration monitoring using optical fiber strain sensors", J. Eng. Mech.-ASCE, 133(2), 185-193. https://doi.org/10.1061/(ASCE)0733-9399(2007)133:2(185)
  27. River, The Governmental Headquarter of Bridge Construction on Yangtzi (2004), The Design of structural health monitoring system on Run-Yang Yangtzi Bridge (in Chinese), Jiangsu Province, China.
  28. Van der Auweraer, H. and Peeters, B. (2003), "International research projects on structural health monitoring: an overview", Struct. Health Monit., 2(4), 341-358. https://doi.org/10.1177/147592103039836
  29. Vidakovic, B. (2009), Statistical modeling by wavelets, Wiley-interscience.
  30. Wong, C.L., Childs, P.A. and Peng, G.D. (2006), "Multiplexed fibre Fizeau interferometer and fibre Bragg grating sensor system for simultaneous measurement of quasi-static strain and temperature using discrete wavelet transform", Measurement Sci. Technol., 17(2), doi:10.1088/0957-0233/17/2/021.
  31. Xu, Y.L., Guo, W.W., Chen, J., Shum, K.M. and Xia, H. (2007), "Dynamic response of suspension bridge to typhoon and trains. I: Field measurement results", J. Struct. Eng.-ASCE, 133(1), 3-11. https://doi.org/10.1061/(ASCE)0733-9445(2007)133:1(3)
  32. 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

Cited by

  1. Serviceability assessment for long-span suspension bridge based on deflection measurements vol.25, pp.11, 2018, https://doi.org/10.1002/stc.2254
  2. Temperature effect analysis of a long-span cable-stayed bridge based on extreme strain estimation vol.20, pp.1, 2017, https://doi.org/10.12989/sss.2017.20.1.011
  3. Thermal response separation for bridge long-term monitoring systems using multi-resolution wavelet-based methodologies vol.10, pp.3, 2014, https://doi.org/10.1007/s13349-020-00402-7
  4. Experimental investigations on the cross-correlation function amplitude vector of the dynamic strain under varying environmental temperature for structural damage detection vol.39, pp.3, 2014, https://doi.org/10.1177/1461348418820237
  5. Vibration-Based Monitoring for Transverse Cooperative Working Performance of Assembled Concrete Multi-Girder Bridge: System Design, Implementation and Preliminary Application vol.21, pp.3, 2014, https://doi.org/10.1142/s0219455421500437