Alfredo Núñez, Zili Li, Rolf Dollevoet
Transportation Research Board 94th Annual Meeting
Year: January 2015
Location: Washington, USA
fuzzy logic, railway infrastructures, squats
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In this study, the authors use a defect prediction-based methodology to support maintenance decisions for railway infrastructure that are related to surface defects known as squats. The performance and cost-effectiveness of possible squat maintenance countermeasures are assessed by analysing scenarios for the evolution of detected squats. Thus, indicators are identified that can enable an infrastructure manager to determine which sections of the track are healthy and which sections require grinding or replacement. To support the decision-making process, a fuzzy expert system is developed to determine the health condition of the tracks and cluster of squats, to facilitate corrective maintenance planning. The benefits of the developed approach are demonstrated by considering a section of the Groningen-Assen track of the Dutch railway network.