Geospatial and temporal data mining to combine railway low adhesion and rail defect data

Rolling contact fatigue (RCF) damage to rails, and low adhesion at the rail-wheel interface remain significant problems in maintaining railway performance, fully utilising network capacity, and reducing running costs. A novel approach has been developed to understand these problems through analysis of data on RCF and low adhesion incidents from the UK rail network. This augments understanding of specific mechanisms such as the role of rail plasticity in crack initiation and of environmental moisture levels in low adhesion, which to-date have not given sufficient information to prevent the problems. A moving window filtering technique, a temporal and a geospatial approach were used to identify correlations between sites of low rail-wheel adhesion subject to transient sliding contact, crack initiation, and underbridge locations at which vertical and lateral track stiffness typically change rapidly. The analysis shows that (i) a high density of otherwise unexpected RCF defects occurred close to underbridges, and (ii) that there was a strong correlation between momentary slides during braking and RCF sites. From the temporal analysis it was found that although concentrated in the autumn period, 55-60% of transient low adhesion incidents occur outside that period, with highest risk in the very early morning.