Ballast Condition Monitoring for Turnouts Using Power Spectral Density
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 9
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.
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Data Availability Statement
Some data, models, or code generated or used during the study are available from the corresponding author by request, which includes the CoMPAcT algorithm for positioning the measurement data in the necessary manner.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 146 • Issue 9 • September 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Feb 28, 2020
Accepted: May 14, 2020
Published online: Jul 8, 2020
Published in print: Sep 1, 2020
Discussion open until: Dec 8, 2020
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