Health Assessment of Railway Turnouts: A Case Study



Published Jul 5, 2016
Allegra Alessi Piero La-Cascia Benjamin Lamoureux Michele Pugnaloni Pierre Dersin


Within railway infrastructure, railway point systems are among the most critical equipment, not only due to accidents and delays caused by their failures but also due to maintenance costs. The detection of early signs of degradation and the ability to identify the maintenance actions required to prevent a failure are key aspects of a successful and advantageous health assessment strategy. While studies focusing on the detection and prognostics of railway point systems exist, few or none address the correlation between environment, field layout and the point system behavior. This paper aims to consider the interaction between these factors and the point system behavior, and compare a fleet-based approach to an asset-based approach for the point systems health assessment, highlighting the influence of the field configuration on the effectiveness of the two methods. The proposed methods exploit Self-Organizing Maps (SOMs) to construct a health indicator for both the detection and the diagnosis of railway point systems. The approaches are applied to a case study for the on-line health assessment of 20 electro-mechanical point systems operating on a main line over the course of 6 months. The results show how an asset-based monitoring system is necessary in order to maintain a level of information which enables to achieve an efficient detection of anomalies and a correct identification of degradation mechanisms. In addition, fleet-based health assessment leads to a higher percentage of missed alarms, due to the intrinsic hypothesis of considering all point systems as operating in the same context and mission profile.

How to Cite

Alessi, A., La-Cascia, P., Lamoureux, B., Pugnaloni, M., & Dersin, P. (2016). Health Assessment of Railway Turnouts: A Case Study. PHM Society European Conference, 3(1).
Abstract 260 | PDF Downloads 228



anomaly detection, PHM, Self-organizing maps, Railway turnouts, fleet-based, asset-based

Asada, T., Roberts. C., Koseki, T. (2013). An algorithm for improved performance of railway condition monitoring equipment: Alternating-current point machine case study. Transportation Research Part C, 30, pp.81-92.
Eker, O., Camci, F., Guclu, A., Yilboga, Y., Sevkli, M., Baskan, S. (2011) A Simple State-Based Prognostic Model for Railway Turnout Systems. IEEE Transactions on Industrial Electronics, vol. 58, no. 5, pp. 1718-1726. doi: 10.1109/TIE.2010.2051399
Gupta, A. & Lawsirirat, C. (2006). Strategically optimum maintenance of monitoring-enabled multi-component systems using continuous-time jump deterioration models’. Journal of Quality in Maintenance Engineering, Vol. 12, No. 3, pp.306–329.
Kohonen, T. (1995). Self-Organizing Maps. Springer Series in Information Sciences.
Letot, C., Dersin, P., Pugnaloni, M., Dehombreux, P., Fleurquin, G., Douziech, C., La-Cascia, P. (2015). A data driven degradation-based model for the maintenance of turnouts: a case study. IFAC-PapersOnLine, Vol. 48, Issue 21, Pages 958-963.
Márquez, F.G.P., Lewis, R. W., Tobias, A.M., Roberts, C. (2008). Life cycle costs for railway condition monitoring. Transportation Research Part E: Logistics and Transportation Review, 44, issue 6, pp. 1175-1187.
Márquez, F.G.P., Weston, P., Roberts, C. (2007). Failure analysis and diagnostics for railway trackside equipment. Engineering Failure Analysis, issue 14, pp. 1411–1426.
Network Rail (2014). Annual Return 2014.
Tobias, A.M., Márquez, F.G.P., Roberts, C. (2010). Railway point mechanisms: condition monitoring and fault detection. Proceedings of the institution of Mechanical Engineerings Part F – Journal of Rail and Rapid Transit 224, pp. 35-44.
Vileiniskis, M., Remenyte-Prescott, R., Rama, D. (2015). A fault detection method for railway point systems. Proceedings of the institution of Mechanical Engineerings Part F – Journal of Rail and Rapid Transit issue 0, pp. 1-14.
Zwanengburg, W. J. (2006). Degradation Processes of Switches & Crossings. Railway Condition Monitoring,. The Institution of Engineering and Technology International Conference on, Birmingham, 2006, pp. 115-119.
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