DOI QR코드

DOI QR Code

Field monitoring of the train-induced hanger vibration in a high-speed railway steel arch bridge

  • Ding, Youliang (School of Civil Engineering, Key Laboratory of C&PC Structures of the Ministry of Education, Southeast University) ;
  • An, Yonghui (Department of Civil Engineering, State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology) ;
  • Wang, Chao (School of Civil Engineering, Key Laboratory of C&PC Structures of the Ministry of Education, Southeast University)
  • Received : 2015.11.23
  • Accepted : 2016.04.19
  • Published : 2016.06.25

Abstract

Studies on dynamic characteristics of the hanger vibration using field monitoring data are important for the design and evaluation of high-speed railway truss arch bridges. This paper presents an analysis of the hanger's dynamic displacement responses based on field monitoring of Dashengguan Yangtze River Bridge, which is a high-speed railway truss arch bridge with the longest span throughout the world. The three vibration parameters, i.e., dynamic displacement amplitude, dynamic load factor and vibration amplitude, are selected to investigate the hanger's vibration characteristics in each railway load case including the probability statistical characteristics and coupled vibration characteristics. The influences of carriageway and carriage number on the hanger's vibration characteristics are further investigated. The results indicate that: (1) All the eight railway load cases can be successfully identified according to the relationship of responses from strain sensors and accelerometers in the structural health monitoring system. (2) The hanger's three vibration parameters in each load case in the longitudinal and transverse directions have obvious probabilistic characteristics. However, they fall into different distribution functions. (3) There is good correlation between the hanger's longitudinal/transverse dynamic displacement and the main girder's transverse dynamic displacement in each load case, and their relationships are shown in the hysteresis curves. (4) Influences of the carriageway and carriage number on the hanger's three parameters are different in both longitudinal and transverse directions; while the influence on any of the three parameters presents an obvious statistical trend. The present paper lays a good foundation for the further analysis of train-induced hanger vibration and control.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation

References

  1. Acampora, A., Macdonald, J.H.G., Georgakis, C.T. and Nikitas, N. (2014), "Identification of aeroelastic forces and static drag coefficients of a twin cable bridge stay from full-scale ambient vibration measurements", J. Wind Eng. Ind. Aerod., 124, 90-98. https://doi.org/10.1016/j.jweia.2013.10.009
  2. An, Y.H., Blachowski, B. and Ou, J.P. (2016), "A degree of dispersion-based damage localization method", Struct. Control Health Monit., 23, 176-192. https://doi.org/10.1002/stc.1760
  3. An, Y.H., Ou, J.P., Li, J. and Spencer, B.F. (2014), "Stochastic DLV method for steel truss structures: Simulation and experiment", Smart Struct. Syst., 14(2), 105-128. https://doi.org/10.12989/sss.2014.14.2.105
  4. An, Y.H., Spencer, B.F. and Ou, J.P. (2015), "A test method for damage diagnosis of suspension bridge suspender cables", Comput. -Aided Civil Infrastruct. E., 30(10), 771-784. https://doi.org/10.1111/mice.12144
  5. Antony, S. and Matthew, G.K. (2002), "Modeling duration of urban traffic congestion", J. Transportation Eng., 128(6), 587-590. https://doi.org/10.1061/(ASCE)0733-947X(2002)128:6(587)
  6. Bayraktar, A., Altunisik, A.C., Sevim, B. and Turker, T. (2010), "Finite element model updating of Komurhan Highway Bridge based on experimental measurements", Smart Struct. Syst., 6(4), 373-388. https://doi.org/10.12989/sss.2010.6.4.373
  7. Chatterjee, P.K. and Datta, T.K. (1995), "Dynamic analysis of arch bridges under travelling loads", Int. J. Solids Struct., 32(11), 1585-1594. https://doi.org/10.1016/0020-7683(94)00193-Z
  8. Chen, Z.Q., Liu, M.G., Hua, X.G. and Mou, T.M. (2011), "Flutter, galloping, and vortex-induced vibrations of H-section hangers", J. Bridge Eng. - ASCE, 17(3), 500-508. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000268
  9. Chiu, Y.T., Lin, T.K., Hung, H.H., Sung, Y.C. and Chang, K.C. (2014), "Integration of in-situ load experiments and numerical modeling in a long-term bridge monitoring system on a newly-constructed widened section of freeway in Taiwan", Smart Struct. Syst., 13(6), 1015-1039. https://doi.org/10.12989/sss.2014.13.6.1015
  10. Ding, Y.L., An, Y.H. and Wang, C. (2015), "Long-term monitoring and analysis of hanger vibration of a high-speed railway steel truss arch bridge", Proceedings of the 2015 World Congress on Advances in Structural Engineering and Mechanics (ASEM15), Incheon, Korea, 25-29 August, 2015.
  11. Feng, M.Q., Chen, Y.B. and Tan, C.A. (2005), "Global structural condition assessment of highway bridges by ambient vibration monitoring". Proc. SPIE 5769, Nondestructive Detection and Measurement for Homeland Security III, 5769, 111-125.
  12. Ju, S.H. and Lin, H.T. (2003), "Numerical investigation of a steel arch bridge and interaction with high-speed trains", Eng. Struct., 25(2), 241-250. https://doi.org/10.1016/S0141-0296(02)00148-7
  13. Katani, R. and Shahmorad, S. (2012), "A block by block method with Romberg quadrature for the system of Urysohn type Volterra integral equations", Eng. Anal. Bound. Elemen., 35(1), 129-139.
  14. Li, H., Ou, J.P., Zhang, X.G., Pei, M. S. and Li, N. (2015b), "Research and practice of health monitoring for long-span bridges in the mainland of China", Smart Struct. Syst., 15(3), 555-576. https://doi.org/10.12989/sss.2015.15.3.555
  15. Li, J., Hao, H. and Lo, J.V. (2015c), "Structural damage identification with power spectral density transmissibility: numerical and experimental studies", Smart Struct. Syst., 15(1), 15-40. https://doi.org/10.12989/sss.2015.15.1.015
  16. Li, J., Hao, H., Fan, K.Q. and Brownjohn, J. (2015a), "Development and application of a relative displacement sensor for structural health monitoring of composite bridges", Struct. Control Health Monit., 22(4), 726-742. https://doi.org/10.1002/stc.1714
  17. Liu, Z.J., Li, Y.H., Tang, L.Q., Liu, Y.P., Jiang, Z.Y. and Fang, D.N. (2014), "Localized reliability analysis on a large-span rigid frame bridge based on monitored strains from the long-term SHM system", Smart Struct. Syst., 14(2), 209-224. https://doi.org/10.12989/sss.2014.14.2.209
  18. Malm, R. and Andersson, A. (2006), "Field testing and simulation of dynamic properties of a tied arch railway bridge", Eng. Struct., 28(1), 143-152. https://doi.org/10.1016/j.engstruct.2005.07.011
  19. Ni, Y.Q., Hua, X.G., Wong, K.Y. and Ko, J.M. (2007), "Assessment of bridge expansion joints using long-term displacement and temperature measurement", J. Perform. Constr. Fac., 21(2), 143-151. https://doi.org/10.1061/(ASCE)0887-3828(2007)21:2(143)
  20. Ni, Y.Q., Ye, X.W. and Ko, J.M. (2006), "Fatigue reliability analysis of a suspension bridge using long-term monitoring data", Key Eng. Mater., 321-323, 223-229. https://doi.org/10.4028/www.scientific.net/KEM.321-323.223
  21. Norouzi, M., Hunt, V. and Helmicki, A. (2013), "Abnormal behavior detection in the Jeremiah Morrow Bridge based on the long term measurement data patterns". Proc. SPIE 8695, Health Monitoring of Structural and Biological Systems 2013, 869536.
  22. Pinkaew, T. and Senjuntichai, T. (2009), "Fatigue Damage Evaluation of Railway Truss Bridges from Field Strain Measurement", Adv. Struct. Eng., 12(1), 53-69. https://doi.org/10.1260/136943309787522632
  23. Saito, T. and Sakata, H. (1999), "Aerodynamic stability of long-span box girder bridges and anti-vibration design considerations", J. Fluids Struct., 13(7), 999-1016. https://doi.org/10.1006/jfls.1999.0238
  24. Shao, Y., Sun, Z.G., Chen, Y.F. and Li, H.L. (2015), "Impact effect analysis for hangers of half-through arch bridge by vehicle-bridge coupling", Struct. Monit. Maint., 2(1), 65-75. https://doi.org/10.12989/SMM.2015.2.1.065
  25. The Math Works Inc. Statistic ToolboxTM 7 user's guide [R/OL]. 2010. http://www.mathworks.cn/help/releases/R13sp2/pdf_doc/stats/stats.pdf
  26. Wang, G.X., Ding, Y.L., Song, Y.S., Wu, L.Y., Yue, Q. and Mao, G.H. (2015), "Detection and location of the degraded bearings based on monitoring the longitudinal expansion performance of the main girder of the Dashengguan Yangtze Bridge", J. Perform. Constr. Fac., 04015074.
  27. 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, 204-213.
  28. 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
  29. Zeng, Y. and Tan, H.M. (2012), "Reliability Assessment of Fatigue Life of Hangers in Large-Span Suspension Bridges", Appl. Mech. Mater., 147, 149-152.
  30. Zhou, L.R., Yan, G.R., Wang, L. and Ou, J.P. (2013). "Review of benchmark studies and guidelines for structural health monitoring", Adv. Struct. Eng., 16(7), 1187-1206. https://doi.org/10.1260/1369-4332.16.7.1187

Cited by

  1. Fast Warning Method for Rigid Hangers in a High-Speed Railway Arch Bridge Using Long-Term Monitoring Data vol.31, pp.6, 2017, https://doi.org/10.1061/(ASCE)CF.1943-5509.0001097
  2. Deployment of a Smart Structural Health Monitoring System for Long-Span Arch Bridges: A Review and a Case Study vol.17, pp.9, 2017, https://doi.org/10.3390/s17092151
  3. Fatigue Behavior Evaluation of Full-Field Hangers in a Rigid Tied Arch High-Speed Railway Bridge: Case Study vol.23, pp.5, 2018, https://doi.org/10.1061/(ASCE)BE.1943-5592.0001235
  4. Finite element model calibration of a steel railway bridge via ambient vibration test vol.27, pp.3, 2016, https://doi.org/10.12989/scs.2018.27.3.327
  5. Wheel tread defect detection for high-speed trains using FBG-based online monitoring techniques vol.21, pp.5, 2016, https://doi.org/10.12989/sss.2018.21.5.687
  6. Structural health monitoring of a high-speed railway bridge: five years review and lessons learned vol.21, pp.5, 2016, https://doi.org/10.12989/sss.2018.21.5.695
  7. CNN-based damage identification method of tied-arch bridge using spatial-spectral information vol.23, pp.5, 2019, https://doi.org/10.12989/sss.2019.23.5.507
  8. Digital Twin Aided Vulnerability Assessment and Risk-Based Maintenance Planning of Bridge Infrastructures Exposed to Extreme Conditions vol.13, pp.4, 2016, https://doi.org/10.3390/su13042051