Abstract
Turnouts are necessary, frequent and cost intensive. Despite the railway sector's focus on automation, the condition assessment of turnouts is still mostly done manually by responsible staff inspecting the turnout. While system's safety is guaranteed by this approach, drawbacks are high costs, subjectivity of assessments and a missing opportunity of prognoses. Most importantly, we will not expect to have the workforce for this regime in future years. By assisting responsible staff with data-based quality assessments, save and time optimised inspection can also be guaranteed with labour force reductions. For providing this, we use data from the track recording car, apply a post positioning procedure and calculate quality indices describing track geometry quality of turnouts in an objective way. The visualisation of these indices over time lead to data sheets which can be used by the responsible staff for maintenance planning. Additionally, the indices build the basis for predictive maintenance regimes for turnouts and open several possibilities for practical and academic enhancements regarding asset management of turnouts.
Published Version
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