RailWear Estimation for Predictive Maintenance: a strategic approach
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Abstract
Since the very beginning of rail transport, wear has been identified as one of the dominant damage mechanisms that influence the Remaining Useful Life (RUL) of rail tracks. Whereas maintenance of the track is now predominantly executed at fixed intervals or based on yearly inspections, the accurate prediction of rail wear could considerably improve the maintenance process. The present work proposes a method for long-term rail wear prediction using measurements of actual rail and wheel profiles as starting point. By doing so, the computational expensive step of updating the rail profile in a wear calculation, as is done in presently used methods, can be omitted. The proposed method is used to study a number of generic trends, varying curve radius and rail or wheel profile. Further, the method is validated against measured wear on actual track sections for moderate curves. Finally, it can easily be extended to include variations in operational usage of the track (type / weight of trains, geometric details, slip conditions) in the future. The method presented in this paper can therefore assist in improving the track maintenance process by maximizing the utilization of the track service life, and minimizing maintenance costs.
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rail wear, vehicle dynamics, prognostics, maintenance
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