Spatial–Temporal Model to Identify the Deformation of Underlying High-Speed Railway Infrastructure
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 8
Abstract
Railway track geometry is generally understood to be influenced by the deformation of the track infrastructure. This study developed a spatial–temporal identification model for the deformation of the underlying high-speed railway infrastructure, including simply supported beams and track slabs based upon track geometry data collected between 2016 and 2019. To achieve this, we first preprocessed the data, including data collection and cleaning. Next, we developed a track irregularity degradation indicator (TIDI) for different track infrastructures using wavelet coefficients. Then, we combined the TIDIs of 40 inspection runs over 3 years to obtain the TIDI distribution matrixes in the spatial and temporal domains for different track infrastructures. In the spatial domain, we extracted the most probable abnormal position of the track slab using kernel density estimation. In the temporal domain, we developed a logarithmic–linear regression model and noted that the growth trend of the TIDI of the abnormal bridge gradually slows with time.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions.
•
Track geometry data are owned by China Railway Chengdu Bureau Group. They are proprietary and require permission for distribution.
Acknowledgments
This study was funded by the China Natural Science Foundation (CNSF) under Grant No. 51878576. The authors would like to express their sincere thanks for the support from the CNSF.
References
Alsahli, A., M. Z. Allan, W. P. Joseph, and L. E. Todd. 2019. “Investigation of the correlation between track geometry defect occurrence and wood tie condition.” Transp. Infrastruct. Geotechnol. 6 (3): 226–244. https://doi.org/10.1007/s40515-019-00077-8.
Berawi, A. R. B., R. Delgado, R. Calçada, and C. Vale. 2010. “Evaluating track geometrical quality through different methodologies.” Int. J. Technol. 1 (1): 38–47.
Cañete, E., J. Chen, M. Díaz, L. Llopis, and B. Rubio. 2019. “Wireless sensor networks and structural health monitoring: Experiences with slab track infrastructures.” Int. J. Distrib. Sens. Netw. 15 (3): 1550147719826002. https://doi.org/10.1177/1550147719826002.
Ghofrani, F., R. Qing He, M. P. Goverde, and X. Liu. 2018. “Recent applications of big data analytics in railway transportation systems: A survey.” Transp. Res. Part C: Emerg. Technol. 90 (May): 226–246. https://doi.org/10.1016/j.trc.2018.03.010.
Gospodnetic, D. 1959. “Deflection curve of a simply supported beam.” ASME, J. Appl. Mech 26 (4): 675–676.
Gou, H. Y., L. C. Yang, Dan Leng, Yi Bao, and Q. H. Pu. 2018. “Effect of bridge lateral deformation on track geometry of high-speed railway.” Steel Compos. Struct. 29 (2): 219–229.
Lasisi, A., and N. Attoh-Okine. 2018. “Principal components analysis and track quality index: A machine learning approach.” Transp. Res. Part C: Emerg. Technol. 91 (Jun): 230–248. https://doi.org/10.1016/j.trc.2018.04.001.
Mohammadi, R., Q. He, F. Ghofrani, A. Pathak, and A. Aref. 2019. “Exploring the impact of foot-by-foot track geometry on the occurrence of rail defects.” Transp. Res. Part C: Emerg. Technol. 102 (May): 153–172. https://doi.org/10.1016/j.trc.2019.03.004.
Molodova, M., Z. Li, A. Núñez, and R. Dollevoet. 2014. “Automatic detection of squats in railway infrastructure.” IEEE Trans. Intell. Transp. Syst. 15 (5): 1980–1990. https://doi.org/10.1109/TITS.2014.2307955.
Nagarajaiah, S., and B. Basu. 2009. “Output only modal identification and structural damage detection using time frequency & wavelet techniques.” Earthquake Eng. Vib. 8 (4): 583–605. https://doi.org/10.1007/s11803-009-9120-6.
National Bureau of Statistics of China. 2020. “Basic statistics of high-speed railway.” Accessed October 17, 2019. http://www.stats.gov.cn/tjsj/ndsj/2018/indexeh.htm.
Ng, A. K., L. Martua, and G. Sun. 2019. “Dynamic modelling and acceleration signal analysis of rail surface defects for enhanced rail condition monitoring and diagnosis.” In Proc., 2019 4th Int. Conf. on Intelligent Transportation Engineering (ICITE), 69–73. New York: IEEE.
Ngamkhanong, C., S. Kaewunruen, and B. J. A. Costa. 2018. “State-of-the-art review of railway track resilience monitoring.” Infrastructures 3 (1): 3. https://doi.org/10.3390/infrastructures3010003.
Nielsen, J. C. O., and X. Li. 2018. “Railway track geometry degradation due to differential settlement of ballast/subgrade—Numerical prediction by an iterative procedure.” J. Sound Vib. 412 (Jan): 441–456. https://doi.org/10.1016/j.jsv.2017.10.005.
Pingrui, Z., L. Xueyi, and L. Guan. 2014. “Experimental study of temperature gradient in track slab under outdoor conditions in Chengdu area.” J. Mod. Transp. 22 (3): 148–155. https://doi.org/10.1007/s40534-014-0050-2.
Sheather, S. J., and C. J. Michael. 1991. “A reliable data-based bandwidth selection method for kernel density estimation.” J. R. Stat. Soc.: Series B (Methodological) 53 (3): 683–690.
Shuai, L. I., Y. I. Yangming, and W. Yuan. 2018. “Study on profile line regularity based on the inertial reference method in high-speed railway.” J. Railway Sci. Eng. 15 (8): 1901–1910.
Tatarinov, A., A. Rumjancevs, and V. Mironovs. 2019. “Assessment of cracks in pre-stressed concrete railway sleepers by ultrasonic testing.” Procedia Comput. Sci. 149 (Jan): 324–330. https://doi.org/10.1016/j.procs.2019.01.143.
Timoshenko, S. P., and S. W. Krieger. 1959. Theory of plates and shells. New York: McGraw-hill.
Torrence, C., and P. C. Gilbert. 1998. “A practical guide to wavelet analysis.” Bull. Am. Meteorol. Soc. 79 (1): 61–78. https://doi.org/10.1175/1520-0477(1998)079%3C0061:APGTWA%3E2.0.CO;2.
Wang, Qi-Ang, and Yi-Qing Ni. 2019. “Measurement and forecasting of high-speed rail track slab deformation under uncertain SHM data using variational heteroscedastic gaussian process.” Sensors 19 (15): 3311. https://doi.org/10.3390/s19153311.
Wang, Tao, Hengqiong Jia, Zike Liu, Zhao Wei, Xiao Xie, Shaoliang Wu, and Haiyan Li. 2018. “Experimental study of the gap between track slab and cement asphalt mortar layer in CRTS I slab track.” J. Mod. Transp. 26 (3): 173–178. https://doi.org/10.1007/s40534-018-0168-8.
Xin, W., W. Yuan, and W. Ping. 2018. “Mileage error estimation and correction of track geometry data from track inspection car on high speed railway.” Railway Stand. Des. 62 (7): 46–51.
Xu, Peng, Quan-Xin Sun, Reng-Kui Liu, and Fu-Tian Wang. 2013. “Key equipment identification model for correcting milepost errors of track geometry data from track inspection cars.” Transp. Res. Part C: Emerging Technol. 35 (Oct): 85–103. https://doi.org/10.1016/j.trc.2013.06.006.
Yang, S., Y.-Y. Yang, L. Zhang, J.-Y. Huang, Y.-R. Bai, and X.-C. Lin. 2020. Real time measurement of subgrade settlement in high speed railways with a resolution of 0.25 mm using a laser imaging method. Philadelphia, PA: Old City Publishing.
Yang, W., S. Lian, and Y. Liu. 2006. “Power spectrum fit analysis for railway track irregularities.” J. Tongji Univ. 34 (3): 363.
Yilmazer, P., A. Amini, and M. Papaelias. 2012. “The structural health condition monitoring of rail steel using acoustic emission techniques.” In Proc. 51st Annu. Conf. NDT, 1–12. Daventry, UK: British Institute of Non-Destructive Testing.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 146 • Issue 8 • August 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Dec 13, 2019
Accepted: Mar 25, 2020
Published online: Jun 11, 2020
Published in print: Aug 1, 2020
Discussion open until: Nov 11, 2020
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.