In this paper, a decision support approach is proposed for condition-based maintenance of rails relying on expert-based systems. The methodology takes into account both the actual conditions of the rails (using axle box acceleration measurements and rail video images) and the prior knowledge of the railway track. The approach provides an integrated estimation of the rail health conditions to support the maintenance decisions for a given time period. An expert-based system is defined to analyse interdependency between the prior knowledge of the track (defined by influential factors) and the surface defect measurements over the rail. When the rail health conditions is computed, the different track segments are prioritized, in order to facilitate grinding planning of those segments of rail that are prone to critical conditions. In this paper, real-life rail conditions measurements from the track Amersfoort-Weert in the Dutch railway network are used to show the benefits of the proposed methodology. The results support infrastructure managers to analyse the problems in their rail infrastructure and to efficiently perform a condition-based maintenance decision making. IntroductionThe increase in train traffic and axle loads affect the health conditions of railway infrastructure. Hence, efficient infrastructure monitoring and maintenance is among the major concerns of infrastructure managers in order to improve the performance of railway operations (Åhrén and Parida, 2009). As such, infrastructure health conditions should be monitored and considered in the maintenance decision making process. Effective management of infrastructure health conditions is crucial to guarantee the desired asset quality level (Parida and Chattopadhyay, 2007;Gandomi and Haider, 2015;Zywiel and Oberlechner, 2001). It also plays an important role in meeting the demands for the whole system performance when the infrastructure is upgraded e.g. when increasing traffic capacity, the maintenance regime should be adapted to avoid compromising safety and infrastructure health requirements. To keep the infrastructure system working at an effective level, a conditions-based maintenance system is required not only to consider the actual heath conditions but also evolution during the maintenance decision horizon (Jamshidi et al., 2017b;Li et al., 2014).Condition-based monitoring is used in railway infrastructures to estimate the actual health conditions of the assets, so that degradation processes can be effectively controlled. It helps to keep the infrastructure manager continually informed of the estimated health of the railway infrastructure. Condition-based monitoring is supposed to collect information that will allow an effective https://doi.

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Employing a dynamic model of the railway wagon in three dimensions, this paper presents the results of dynamic wheel–rail forces under the presence of track irregularities. A mathematical model of the wagon system is developed using dynamic equations of the components, taking into account the vertical (bounce), pitch and roll motions of the system. The model examines the dynamics of the wagon system under arbitrary rail irregularities. The spectra of rail surface irregularities are fed into the vehicle model to extract the time histories of dynamic forces between the wheel and the rail. Using the irregularity spectra of left/right rails, vibration of the wheelsets is studied for the bounce–roll motions. The dynamic contact forces between wheels and rails are determined for three examples of the measured irregularities. Moreover, three V-shape defects are modelled as examples of the singular defects on rail surface. The results of dynamic simulations confirm the large amounts of impact forces due to the presence of rail irregularities, particularly for the cases with much unevenness between the left/right profiles.