A Bayesian Network Approach for Condition Monitoring of High-Speed Railway Catenaries

The growing variety of data from condition monitoring of high-speed railways offer unprecedented opportunities to improve railway infrastructure maintenance. For condition monitoring of railway catenaries, this paper proposes a data-driven approach that uses a Bayesian network (BN) to integrate the inspection data from catenaries into a key...

Method for evaluating the performance of railway crossing rails after long-term service

In this paper, we present a method for evaluating the performance of railway crossing rails after long-term service. The method includes 1) 3D profile and hardness measurements; 2) finite element simulation of wheel/rail interaction; and 3) numerical prediction of rail degradation. We conducted a case study on a crossing that had been in service...

Robust and predictive fuzzy key performance indicators for condition-based treatment of squats in railway infrastructures

This paper presents a condition-based treatment methodology for a type of rail surface defect called squat. The proposed methodology is based on a set of robust and predictive fuzzy key performance indicators. A fuzzy Takagi-Sugeno interval model is used to predict squat evolution for different scenarios over a time horizon. Models including...

Key performance indicators using robust prediction modelling to consider squats in railway infrastructure