Publication Cover
Structure and Infrastructure Engineering
Maintenance, Management, Life-Cycle Design and Performance
Volume 16, 2020 - Issue 8
1,759
Views
10
CrossRef citations to date
0
Altmetric
Articles

Investigation of the effect of the inspection intervals on the track geometry condition

, , &
Pages 1138-1146 | Received 17 May 2019, Accepted 03 Sep 2019, Published online: 20 Nov 2019

References

  • Albisua, I., Arbelaitz, O., Gurrutxaga, I., Lasarguren, A., Muguerza, J., & Pérez, J. M. (2013). The quest for the optimal class distribution: an approach for enhancing the effectiveness of learning via resampling methods for imbalanced data sets. Progress in Artificial Intelligence, 2(1), 45–63. doi:10.1007/s13748-012-0034-6
  • Andrade, A. R., & Teixeira, P. F. (2013). Unplanned-maintenance needs related to rail track geometry. Proceedings of the Institution of Civil Engineers - Transport, 167(6), 400–410. doi:10.1680/tran.11.00060
  • Andrews, J., Prescott, D., & De Rozières, F. (2014). A stochastic model for railway track asset management. Reliability Engineering & System Safety, 130, 76–84. doi:10.1016/j.ress.2014.04.021
  • Arasteh Khouy, I., Larsson-Kråik, P., Nissen, A., Juntti, U., & Schunnesson, H. (2014). Optimisation of track geometry inspection interval. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 228(5), 546–556.
  • AREMA. (2006). Manual for railway engineering (Report No. 4). American Railway Engineering and Maintenance-of-Way Association USA.
  • Cárdenas-Gallo, I., Sarmiento, C. A., Morales, G. A., Bolivar, M. A., & Akhavan-Tabatabaei, R. (2017). An ensemble classifier to predict track geometry degradation. Reliability Engineering & System Safety, 161, 53–60.
  • EN 13848–5. (2008). Railway applications – track – track geometry quality – Part 5: Geometric quality levels. Brussels, Belgium: CEN (European Committee for Standardization).
  • Haixiang, G., Yijing, L., Shang, J., Mingyun, G., Yuanyue, H., & Bing, G. (2017). Learning from class-imbalanced data: review of methods and applications. Expert Systems with Applications, 73, 220–239.
  • He, H., Bai, Y., Garcia, E. A., & Li, S. (2008). ADASYN: adaptive synthetic sampling approach for imbalanced learning. Paper presented at 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), Hong Kong, China.
  • Hosmer, D. W., Jr, Lemeshow, S., & Sturdivant, R. X. (2013). Applied logistic regression. Hoboken: John Wiley & Sons.
  • Loyola-González, O., Martínez-Trinidad, J. F., Carrasco-Ochoa, J. A., & García-Borroto, M. (2016). Study of the impact of resampling methods for contrast pattern based classifiers in imbalanced databases. Neurocomputing, 175, 935–947.
  • Lyngby, N., Hokstad, P., & Vatn, J. (2008). RAMS management of railway tracks. In Handbook of performability engineering (pp. 1123–1145). London: Springer.
  • Meier-Hirmer, C., Sourget, F., & Roussignol, M. (2005). Optimising the strategy of track maintenance. Paper presented at Advances in Safety and Reliability, proceedings of ESREL 2005-European Safety and Reliability Conference 2005, Tri City (Gdynia–Sopot–Gdańsk), Poland.
  • Osman, M. H. B., Kaewunruen, S., Jack, A., & Sussman, J. (2016). Need and opportunities for a ‘Plan B’ in rail track inspection schedules. Procedia Engineering, 161, 264–268.
  • Quiroga, L. M., & Schnieder, E. (2012). Monte Carlo simulation of railway track geometry deterioration and restoration. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 226(3), 274–282. doi:10.1177/1748006X11418422
  • Soleimanmeigouni, I., Ahmadi, A., & Kumar, U. (2018). Track geometry degradation and maintenance modelling: a review. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 232(1), 73–102.
  • Soleimanmeigouni, I., Ahmadi, A., Letot, C., Nissen, A., & Kumar, U. (2016). Cost-based optimization of track geometry inspection. Paper presented at 11th World Congress of Railway Research, Milan, Italy.
  • Soleimanmeigouni, I., Xiao, X., Ahmadi, A., Xie, M., Nissen, A., & Kumar, U. (2018). Modelling the evolution of ballasted railway track geometry by a two-level piecewise model. Structure and Infrastructure Engineering, 14(1), 33–45.
  • SS-EN 13848-1: 2004 + A1. (2008). Railway applications – track – track geometry quality –Part 1 Characterisation of track geometry. Sweden: Swedish Standard Institute.
  • Sun, Y., Kamel, M. S., Wong, A. K., & Wang, Y. (2007). Cost-sensitive boosting for classification of imbalanced data. Pattern Recognition, 40(12), 3358–3378.
  • Trafikverket. (2015). Banöverbyggnad – Spårläge – Krav vid Byggande och Underhåll (Track superstructure – Track geometry – Requirements after renewal and maintenance, in Swedish). TDOK 2013:0347 v3.0. Borlänge, Sweden: Trafikverket.
  • UIC. (2008). Best practice guide for optimum track geomerty durability. Paris, France: ETF - Railway Technical Publications.
  • Zaayman, L. (2017). The basic principles of mechanized track maintenance (3rd ed.). Bingen am Rhein: PMC Media House. doi:978-3-96245-151-6.