Railway track support condition assessment: from onboard measurement to maintenance decision support 

Abstract

The railway track is the most critical element that infrastructure managers have to ensure satisfactory health conditions to provide safe, sustainable, and adequate service quality. The condition of railway tracks is managed through maintenance strategies that benefit enormously from the availability of accurate and updated information from measurement devices. This thesis focuses on estimating the track support condition using Axle Box Acceleration (ABA) measurements. The ABA characteristics under different track support conditions are evaluated, effects of influential parameters in the measurements are analyzed, key performance indicators (KPIs) for condition monitoring of ballast and substructure layers are proposed, and results with traditional techniques such as impact tests are compared. Finally, an enhanced track quality index is proposed to improve the effectiveness of maintenance decision-making. Case studies in The Netherlands, Sweden, and Norway are considered.