Railway Track Quality Assessment And Related Decision Making

Railway Track Quality Assessment and Related Decision Making
Stasha Jovanovic Delft University of Technology, Faculty of Civil Engineering & Geosciences, Road and Railway Engineering Group, The Netherlands

ABSTRACT: Maintenance and renewal (M&R) of railway networks require significant investments. For example the annual expenditure for the Dutch Infra Provider “ProRail” permanent way (3,500kmof tracks) amounts to about EUR (€) 180 million (price level 2000) (1). It is completely clear that even marginal improvements in € the efficiency of the Maintenance Management can yield large absolute savings.

In order to keep the Railway Infrastructure (RI) in the satisfactory condition, the manner in which this condition of every single RI element changes, must be properly understood.Understanding this change in condition in fact means understanding the behavior of RI objects, which paves the way towards predicting it. In order to relate the observed (captured) behavior in the past with the predicted behavior in the future, so called “deterioration models” are needed.

The research presented in this paper describes a generic/universal deterioration model that was developedspecifically so that it would be flexible enough to be applicable to any parameter’s deterioration, yet powerful and flexible enough to accurately represent/fit various condition behaviors.

Developing such a generic deterioration model and empowering it with LCC and numerical optimization techniques, and incorporating them all in a suitable, powerful yet flexible, Track Maintenance Management System(TMMS) or full-scale Asset Management System (AMS), allows Railways to perform true long-term simulations of the track behavior, balancing effectively achieved quality with the costs of M&R works, inspections and other consequences like traffic disruptions, availability, etc., enabling significant cost-savings.

BASIC DATA NEEDED FOR PREDICTION AND PLANNING Track Maintenance Management Systems(TMMS) logically represent constitutive part of Railway Asset Management Systems (AMS). However, until Railway AMS become sufficiently developed and fully accepted as a concept, TMMS will exist more as stand-alone systems. Even as stand-alone, if designed properly, they represent invaluable tools for any track and/or infrastructure manager. In order to properly manage track maintenance a vastamount of data is needed. Types of data to be collected for computeraided TMMS are summarized in Figure 1.

However, with such a big diversity of information frequently changing along thousands of kilometers of railway networks, a question arises as to how effectively to utilize all this information in order to understand and model the behavior of railway infrastructure assets. The answer to thisquestion lies in the Segmentation process, by which the linear infrastructure is divided into segments, and all abovementioned information is aggregated and associated to them. Segments’ lengths typically differ between different infrastructure objects (e.g. track and overhead line wire), in order to better conform both to the respective deterioration patterns as well as to the establishedmaintenance practices. For example, for track, in most cases these lengths historically corresponded to the segment lengths for which (now already old-fashioned) track-recording cars produced statistically processed data (e.g. standard deviations and quality indices), which were historically 100 or 200 m, or alternatively on a kilometer basis. For overhead line wire however, these lengths were usually keptat the kilometric level, due to the fact that the wires were usually installed in those lengths. But, these kinds of “fixed segmentations” were much too rigid to conform to the actual change of behavior as seen along the track, for which reason, more sophisticated segmentation concepts were needed.

TRACK SEGMENTATION It is has been long established that track segments with nominally...