Abstract

The European initiative Shift2Rail (S2R) joins efforts for smart and sustainable growth in the railway sector by fostering research and innovation. Specifically, the project FR8RAIL within the Innovation Programme 5 (IP5) 'rail freight' of S2R aims to remove limiting factors of rail freight transportation. The work presented here is part of FR8RAIL and addresses the use and implementation of positioning strategies for rail freight transportation. Freight localization services based on on-board positioning, for example, can facilitate logistic optimization schemes that rely on continuous position and speed information. No extra trackside infrastructure is required, which reduces implementation and maintenance costs. The paper describes the challenges and requirements of on-board positioning strategies for the use in rail freight transportation and presents solution concepts (positioning requirements, hardware architecture, algorithms) for a more competitive rail freight.

Abstract

Railway switches are crucial for normal operation and during disruptions of the railroad system since they allow trains to use alternative routes. Switches moving parts are subject to high deterioration and prone to malfunctioning, representing a potential safety hazard. Thus frequent inspection, maintenance and renewal are required. Models to optimize the railroad system operation and reduce costs are possible on the basis of inspections vehicles, online condition monitoring, inspection standardization and data-based models. This paper presents a switch condition now- and forecasting model based on continuous monitored data (switch engine current during blades movement). The model is capable of identifying unusual behavior due to emerging failures without the need of manually set switch-specific thresholds. In this approach no labelled training data set of historic switch failures is required for training the model. Its output combined with maintenance information and the switch functional model sheds light on switch degradation modes, helping to optimize maintenance actions.

Abstract

Preventive and condition-based maintenance of rail infrastructure is an important aspect in reducing interruptions and delays in train operations. In case of optimal implementation, it even helps to lower the overall maintenance costs by avoiding expensive instant repairs of sudden failures including possible incidental damages. For being effective in this context, asset managers need to estimate not only the current state of the rail infrastructure and its components but they also need to predict future conditions based on available data and measurements. Stochastic modelling has shown to be a promising way for tackling these tasks. However, uncertainties of the model results need to be evaluated then in order to make maintenance planning as solid as possible. Commonly, Monte Carlo (MC) simulations are used for analyzing the stochastic distributions of the model outputs whenever analytical solutions are not possible or difficult to obtain. In contrast to that, an interesting alternative for numerically deriving important statistical quantities related to the model results (such as mean or standard deviation) is given by the so-called Point Estimate Method (PEM). Depending on the details of the model under consideration, PEM can be shown to be even exact under certain constraints while often requiring just a small number of sample points to be evaluated. In contrast to that, the MC approach naturally yields approximate results only with a potential need for several hundred or thousand sample points in order to converge. The present contribution shortly reviews the mathematical background of PEM before demonstrating its performance based on three more or less academic examples from the wide field of railway asset management: i) track degradation, ii) reliability analysis of composite systems, iii) failure detection/identification using decision trees. Finally, advantages as well as limitations of the PEM approach in comparison to common MC simulations are discussed.