Modelling degradation rates of track geometry local defects: Lisbon-Porto line case study

Abstract

The proper scheduling of track maintenance and renewal operations is dependent on the accuracy of predictive maintenance outputs which, in turn, rely on the appropriate modelling of the track geometry degradation process. This paper explores the incidence and representativeness of the alerts generated due to local defects of track geometry and the modelling of their degradation rates between consecutive tamping operations. A software tool was developed and used to process track inspection data collected over 12 years of operation of the main Portuguese line (Lisbon-Porto) on a total of 727 km of single-track lines where speeds vary between 30 and 220 km/h. Linear regressions are found to be suitable to model the degradation rates of local defects of longitudinal levelling, alignment and twist in the vast majority of cases, although 20–30% of the time degradation patterns prove to be non-linear even in the short term. The local defects of alignment degrade more rapidly and trigger 80% of the unplanned maintenance needs. Modelling the evolution of local defects, and not only the standard deviation on sections 200 m long, allows us to anticipate unplanned maintenance and tackle unavailability costs.

Keywords:

• Decision support systems
• defects
• degradation
• maintenance
• railroad engineering
• railway systems
• regression analysis

Disclosure statement

No potential conflict of interest was reported by the authors.

Acknowledgements

The authors would like to thank the support and collaboration from the Portuguese Railway Infrastructure Manager, Infraestruturas de Portugal (former REFER, E.P.E.). Needless to say that any errors or lapses are entirely the authors’ responsibility.

Additional information

Funding

This work was supported by the Portuguese Foundation for Science and Technology (FCT) under grant PTDC/SENTRA/112975/2009; and Portuguese Foundation for Science and Technology (FCT) under the MIT Portugal Program in Transportation Systems PhD scholarship grant PD/BD/52358/2013.