Ballast Condition Monitoring for Turnouts Using Power Spectral Density

Abstract

Turnouts are important components of railway infrastructure that require more attention as they must be frequently maintained. To transfer the resultingly high investment costs into a correspondingly long service life, the effects of all maintenance decisions must be identified. It is necessary to objectively weigh the impact of all maintenance activities and the optimum point in time for their execution. To make these decisions, information about the condition of the whole system as well as of the individual components must be available. This paper presents a model for describing the current ballast condition based on track measurement data collected by a track recording car. These data include longitudinal level measurements, whereby information on the changes observed in various wavelength ranges can be inferred by means of a power density spectra analysis. Time series analyses of these spectra allow conclusions to be drawn regarding the current condition of the ballast. By applying this method, new information can be collected on the component condition using existing data. In this study, statements could be derived about the ballast conditions at 45 turnouts, and they could be divided into three distinct ballast condition classes.