Abstract
The emergence of systematic condition monitoring of railway infrastructure has the potential to reduce the cost of providing a safe network. The traditional ‘inspect and rectify’ style of maintenance planning is being increasingly complemented by a ‘monitor, predict and prevent’ approach. In order to facilitate this, the frequency of track measurement must be increased from the current periodic measurements using specialised instrumented vehicles. In recent years there has been an increased interest in the challenge of finding railway track longitudinal profile using the response of passing instrumented vehicles as a by-product of regular service. A method is presented where the inertial response of a train bogie is used as input to an optimisation technique that infers the track longitudinal profile. The method finds the track profile that generates a numerical output from a vehicle-track interaction model that best fits a measured response. Experimental data is used to validate the longitudinal profile estimation algorithm. An Irish Rail InterCity train was instrumented to capture in-service vehicle responses. During the testing period, the longitudinal profile of a section of this line featuring a known settlement issue was surveyed by traditional means, for reference. A calibrated vehicle is used in the optimisation algorithm to find the longitudinal profile that generates a numerical vehicle response best fitting the measured data. The known track settlement is found quite well using the calibrated vehicle, thereby validating the method. The reproducibility of the method is assessed. While improvements in accuracy and reproducibility are required to bring the method up to best practice standards, the information provided demonstrates the ability to find localised changes in track profile.
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