Analysis and Modelling of the Track Quality Index of Railways

Abstract

AbstractPublic transportation is vital to the sustainability of urban areas. The benefits associated with rail transportation make it an attractive public transport option for commuters. Efficient maintenance and asset management is required to ensure the condition of railway infrastructure remains at a sufficient level for railway operations to continue without delays or disruptions. A known cause of deteriorating railway tracks is ineffective or absence of maintenance practices. Technological advancements cause an increase in available data in various industries. The railway industry is no exception to this, with geometry measurements such as track quality index (TQI) of permanent way being an example of high volumes of generated data in the railway industry. TQI is an indicator of track condition based on five rail geometric irregularities. Changes in track geometry cause track irregularities, which reduce the quality of railway tracks. TQI data pose challenges during the analysis thereof due to the large number of data entries. This paper investigates the track geometry parameters that are measured as part of the TQI. A quantitative approach is followed to propose a method for analysing TQI data. A case study is conducted on segments of the railway network in Cape Town, South Africa to evaluate the application of the proposed analysis method. The proposed method makes use of data mining techniques along with ArcGIS software and network spatial analysis that takes the network characteristics of a railway network into account. The proposed method of analysis aims to assist railway technicians with their maintenance decision-making to ultimately improve the predictive maintenance and asset management strategies currently in place.KeywordsRailway maintenanceTrack quality indexNetwork spatial analysis