Operational Influence Line Identification of High-Speed Railway Bridge Considering Uncertainty of Train Load
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10, Issue 4
Abstract
The bridge influence line (BIL) contains static information for each section of a bridge, which is an important tool for bridge design and condition evaluation. The current influence line identification procedure relies on periodic load testing using calibrated vehicles and always leads to long-time traffic disruption. To overcome this shortcoming and achieve online tracking of high-speed railway (HSR) bridge influence lines, this paper proposes an operational influence line identification approach for HSR bridges based on train-induced responses only. First, to consider the train load uncertainty during operation, a train load interval model is established based on field investigations. Then, the BIL intervals are determined by interval computations and accumulate to generate a continuously updated database. Finally, the influence line is identified from the BIL interval database using a binary classification algorithm. The proposed method is verified by an example of a three-span girder bridge, and a train–bridge interaction model is established to simulate the bridge responses induced by various train loads. The results show that the proposed approach has similar accuracy as the traditional load testing methods, which can achieve high-accuracy online tracking of HSR bridge influence lines.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
All data, models, or codes generated or used during the study are available from the corresponding author by request.
Acknowledgments
This research work was jointly supported by the National Natural Science Foundation of China (Grant Nos. 52250011, and 52208147), and the Fellowship of China Postdoctoral Science Foundation (Grant No. 2022TQ0053).
References
Alampalli, S., D. M. Frangopol, J. Grimson, M. W. Halling, D. E. Kosnik, E. O. L. Lantsoght, D. Yang, and Y. E. Zhou. 2021. “Bridge load testing: State-of-the-practice.” J. Bridge Eng-ASCE. 26 (3): 03120002. https://doi.org/10.1061/(ASCE)BE.1943-5592.0001678.
Chen, Z. W., Q. L. Cai, and J. Li. 2015. “Damage detection in long suspension bridges using stress influence lines.” J. Bridge Eng. 20 (3): 05014013. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000681.
Chen, Z. W., W. B. Yang, J. Li, T. H. Yi, J. C. Wu, and D. D. Wang. 2019. “Bridge influence line identification based on adaptive B-spline basis dictionary and sparse regularization.” Struct. Control Health Monit. 26 (6): e2355. https://doi.org/10.1002/stc.2355.
Chen, Z. W., L. Zhao, W. J. Yan, K. V. Yuen, and C. Wu. 2022. “A statistical influence line identification method using Bayesian regularization and a polynomial interpolating function.” Struct. Control Health Monit. 29 (11): e3080. https://doi.org/10.1002/stc.3080.
Dai, X., H. Zhao, S. Yu, D. Cui, Q. Zhang, H. Dong, and T. Chai. 2022. “Dynamic scheduling, operation control and their integration in high-speed railways: A review of recent research.” IEEE Trans. Intell. Transp. Syst. 23 (9): 13994–14010. https://doi.org/10.1109/TITS.2021.3131202.
Degrauwe, D., G. Lombaert, and G. De Roeck. 2010. “Improving interval analysis in finite element calculations by means of affine arithmetic.” Comput. Struct. 88 (3): 247–254. https://doi.org/10.1016/j.compstruc.2009.11.003.
Dessombz, O., F. Thouverez, J. P. Lainé, and L. Jézéquel. 2001. “Analysis of mechanical systems using interval computations applied to finite element methods.” J. Sound Vib. 239 (5): 949–968. https://doi.org/10.1006/jsvi.2000.3191.
Ding, S. S., D. W. Chen, and J. L. Liu. 2021. “Research, development and prospect of China high-speed train.” Chin. J. Theor. Appl. Mech. 53 (1): 35–50. https://doi.org/0.6052/0459-1879-20-225.
Du, Y. L., T. H. Yi, X. J. Li, X. L. Rong, L. J. Dong, D. W. Wang, G. Yang, and Z. Leng. 2023. “Advances in intellectualization of transportation infrastructures.” Engineering 23 (4): 64. https://doi.org/10.1016/j.eng.2023.01.011.
Figueiredo, L. H., and J. Stolfi. 2004. “Affine arithmetic: Concepts and applications.” Numer. Algorithms 37 (1): 147–158. https://doi.org/10.1023/B:NUMA.0000049462.70970.b6.
Gonçalves, M. S., R. H. Lopez, E. Oroski, and A. M. Valente. 2022. “A Bayesian algorithm with second order autoregressive errors for B-WIM weight estimation.” Eng. Struct. 250 (Feb): 113353. https://doi.org/10.1016/j.engstruct.2021.113353.
Hansen, E. 1980. “Global optimization using interval analysis—The multi-dimensional case.” Numer. Math. 34 (3): 247–270. https://doi.org/10.1007/BF01396702.
Ieng, S. S. 2015. “Bridge influence line estimation for bridge weigh-in-motion system.” J. Comput. Civ. Eng. 29 (1): 06014006. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000384.
Jian, X. D., Y. Xia, S. W. Sun, and L. M. Sun. 2022. “Integrating bridge influence surface and computer vision for bridge weigh-in-motion in complicated traffic scenarios.” Struct. Control Health Monit. 29 (11): e3066. https://doi.org/10.1002/stc.3066.
Kalhori, H., M. Makki Alamdari, X. Zhu, and B. Samali. 2018. “Nothing-on-road axle detection strategies in bridge-weigh-in-motion for a cable-stayed bridge: Case study.” J. Bridge Eng. 23 (8): 05018006. https://doi.org/10.1061/(ASCE)BE.1943-5592.0001259.
Liu, Y. Z., T. H. Yi, D. H. Yang, H. N. Li, and H. Liu. 2023. “Dynamic amplification factor variation analysis of a high-speed railway bridge under multiple loading cases.” J. Perform. Constr. Facil. 37 (1): 04022077 https://doi.org/10.1061/JPCFEV.CFENG-4236.
Markov, S. 1999. “An iterative method for algebraic solution to interval equations.” Appl. Numer. Math. 30 (2–3): 225–239. https://doi.org/10.1016/S0168-9274(98)00112-3.
Martinez, D., A. Malekjafarian, and E. Obrien. 2020. “Bridge health monitoring using deflection measurements under random traffic.” Struct. Control Health Monit. 27 (9): e2593. https://doi.org/10.1002/stc.2593.
Montenegro, P. A., H. Carvalho, D. Ribeiro, R. Calçada, M. Tokunaga, M. Tanabe, and W. M. Zhai. 2021. “Assessment of train running safety on bridges: A literature review.” Eng. Struct. 241 (Jun): 112425. https://doi.org/10.1016/j.engstruct.2021.112425.
NRA (National Railway Administration of the People’s Republic of China). 2014. PSD of ballastless track irregularities of high-speed railway. TB/T 3352-2014. Beijing: China Railway Publishing House.
OBrien, E. J., M. J. Quilligan, and R. Karoumi. 2006. “Calculating an influence line from direct measurements.” Proc. Inst. Civ. Eng. Bridge Eng. 159 (1): 31–34. https://doi.org/10.1680/bren.2006.159.1.31.
Ojio, T., C. H. Carey, E. J. OBrien, C. Doherty, and S. E. Taylor. 2016. “Contactless bridge weigh-in-motion.” J. Bridge Eng. 21 (7): 04016032 https://doi.org/10.1061/(ASCE)BE.1943-5592.0000776.
Olsson, M. 1991. “On the fundamental moving load problem.” J. Sound Vibr. 145 (2): 299–307. https://doi.org/10.1016/0022-460X(91)90593-9.
Pimentel, R., D. Ribeiro, L. Matos, A. Mosleh, and R. Calçada. 2021. “Bridge weigh-in-motion system for the identification of train loads using fiber-optic technology.” Structures 30 (Apr): 1056–1070. https://doi.org/10.1016/j.istruc.2021.01.070.
Qiu, Z. P., and X. J. Wang. 2005. “Parameter perturbation method for dynamic responses of structures with uncertain-but-bounded parameters based on interval analysis.” Int. J. Solids Struct. 42 (18–19): 4958–4970. https://doi.org/10.1016/j.ijsolstr.2005.02.023.
Rao, S. S., and L. Berke. 1997. “Analysis of uncertain structural systems using interval analysis.” AIAA J. 35 (4): 727–735. https://doi.org/10.2514/2.164.
Reichel, L., and G. Rodriguez. 2013. “Old and new parameter choice rules for discrete ill-posed problems.” Numer. Algorithms 63 (1): 65–87. https://doi.org/10.1007/s11075-012-9612-8.
Renders, H., J. Schoukens, and G. Vilain. 1984. “High-accuracy spectrum analysis of sampled discrete frequency signals by analytical leakage compensation.” IEEE Trans. Instrum. Meas. 33 (4): 287–292. https://doi.org/10.1109/TIM.1984.4315226.
Strauss, A., R. Wendner, D. M. Frangopol, and K. Bergmeister. 2012. “Influence line-model correction approach for the assessment of engineering structures using novel monitoring techniques.” Smart. Struct. Syst. 9 (1): 1–20. https://doi.org/10.12989/sss.2012.9.1.001.
Sujon, M., and F. Dai. 2021. “Application of weigh-in-motion technologies for pavement and bridge response monitoring: State-of-the-art review.” Autom. Constr. 130 (Jun): 103844. https://doi.org/10.1016/j.autcon.2021.103844.
Suykens, J. A. K., and J. Vandewalle. 1999. “Least squares support vector machine classifiers.” Neural Process Lett. 9 (3): 293–300. https://doi.org/10.1023/A:1018628609742.
Ticona Melo, L. R., J. Malveiro, D. Ribeiro, R. Calçada, and T. Bittencourt. 2020. “Dynamic analysis of the train-bridge system considering the non-linear behavior of the track-deck interface.” Eng. Struct. 220 (Jan): 110980. https://doi.org/10.1016/j.engstruct.2020.110980.
Wang, C., and Z. P. Qiu. 2013. “Equivalent method for accurate solution to linear interval equations.” Appl. Math. Mech. 34 (8): 1031–1042. https://doi.org/10.1007/s10483-013-1725-6.
Wei, Y. T., D. H. Yang, T. H. Yi, and H. N. Li. 2023. “Bridge static influence line identification based on structural dynamic responses under high-speed trains.” Int. J. Struct. Stab. Dyn. 23 (11): 2350126. https://doi.org/10.1142/S0219455423501262.
Wei, Y. T., T. H. Yi, D. H. Yang, and H. N. Li. 2021. “Bridge damage localization using axle weight time history data obtained through a bridge weigh-in-motion system.” J. Perform. Constr. Facil. 35 (5): 04021065. https://doi.org/10.1061/(ASCE)CF.1943-5509.0001642.
Yang, Y. B., and K. C. Chang. 2009. “Extraction of bridge frequencies from the dynamic response of a passing vehicle enhanced by the EMD technique.” J. Sound Vib. 322 (4–5): 718–739. https://doi.org/10.1016/j.jsv.2008.11.028.
Zhai, W. M., Z. L. Han, Z. W. Chen, L. Ling, and S. Y. Zhu. 2019. “Train–track–bridge dynamic interaction: A state-of-the-art review.” Veh. Syst. Dyn. 57 (7): 984–1027. https://doi.org/10.1080/00423114.2019.1605085.
Zhang, N., and H. Xia. 2013. “Dynamic analysis of coupled vehicle–bridge system based on inter-system iteration method.” Comput. Struct. 114 (Sep): 26–34. https://doi.org/10.1016/j.compstruc.2012.10.007.
Zheng, X., D. H. Yang, T. H. Yi, and H. N. Li. 2020. “Bridge influence line identification from structural dynamic responses induced by a highspeed vehicle.” Struct. Control Health Monit. 27 (7): e2544. https://doi.org/10.1002/stc.2544.
Zheng, X., D. H. Yang, T. H. Yi, H. N. Li, and Z. W. Chen. 2019. “Bridge influence line identification based on regularized least-squares QR decomposition method.” J. Bridge Eng. 24 (8): 06019004. https://doi.org/10.1061/(ASCE)BE.1943-5592.0001458.
Zheng, X., T. H. Yi, D. H. Yang, and H. N. Li. 2023. “Bridge evaluation based on identified influence lines and influence surfaces: Multiple-scenario application.” Int. J. Struct. Stab. Dyn. 23 (16n18): 2340026. https://doi.org/10.1142/S0219455423400266.
Zhou, Y., Y. L. Pei, Z. W. Li, L. Fang, Y. Zhao, and W. J. Yi. 2020. “Vehicle weight identification system for spatiotemporal load distribution on bridges based on non-contact machine vision technology and deep learning algorithms.” Measurement 159 (Feb): 107801. https://doi.org/10.1016/j.measurement.2020.107801.
Zhou, Y., S. Zhou, G. Hao, and J. Zhang. 2021. “Bridge influence line identification based on big data and interval analysis with affine arithmetic.” Measurement 183 (Sep): 109807. https://doi.org/10.1016/j.measurement.2021.109807.
Information & Authors
Information
Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10 • Issue 4 • December 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Oct 3, 2023
Accepted: Feb 16, 2024
Published online: Jul 18, 2024
Published in print: Dec 1, 2024
Discussion open until: Dec 18, 2024
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.