Project

Bayesian Techniques for Rail Reliability Modelling and Maintenance Decision Support


Host university

QUT

INDUSTRY PARTNERS

THEME ALIGNMENT

Infrastructure Health Monitoring and Predictive Maintenance

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Data collection, security, and integration

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Modelling, Simulations and Prognostics

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INDUSTRY PROBLEM

A key problem with rail infrastructure is the appearance of defects on the rail surface (e.g. squats, worn profiles, contact fatigue). If left unattended, these defects can develop and result in significant safety risk (e.g. derailment). To manage these risks, a number of inspection activities are typically undertaken, including: 1) inspection technologies (e.g. a track recording vehicle) that measure the rail profile; 2) work orders that briefly describe the execution and results of visual inspections; 3) detailed engineering reports with more comprehensive (but less structured) information on defects. The key challenge is to use the information from these multiple data sources to develop a complete statistical picture of the appearance and evolution of critical defects as well as their dependence on factors such as gross tonnage, traffic speed, curvature, etc. Moreover developing and communicating maintenance plans that respect regulatory constraints and resource budgets (e.g. staff, specialized equipment) would be greatly aided by the development of mathematical optimisation techniques — particularly in the case of multiple competing objectives (cost, risk, etc.) — to plan inspections and rail renewals.  


CONTACT CONTRIBUTORS

Michael E. Cholette

Chief Investigator
Queensland University of Technology
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Tommy Chan

RIIS Hub Lead Chief Investigator
Queensland University of Technology
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Joe Mathew

Partner Investigator
Asset Institute
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