Development of improved railway track degradation models

Abstract

There is a need among railway track maintenance programmers for a better understanding of the long-term behaviour of railway track systems and for improved predictive techniques. The use of accurate techniques to predict railway track conditions increases track safety and maintenance effectiveness. The aim of this research is to improve current track deterioration modelling techniques using a comprehensive field investigation. Statistical and engineering approaches are adapted for this research and comprehensive track field data is collected and analysed over a period of 2 years on approximately 100 km of railway line. Parameters that influence track degradation, including loading conditions, track maintenance status and track quality, are investigated, leading to the development of correlations between the effective parameters and the track degradation. These constructed correlations are then used to develop a new track degradation model in two formats. One format, based on track geometry, relies on data obtained from track geometry inspections. The other, based on track structure, relies on data obtained from visual inspections of the track structural conditions.