A Condition-Based Maintenance Methodology for Rails in Regional Railway Networks Using Evolutionary Multiobjective Optimization

Abstract

2018). A condition-based maintenance methodology for rails in regional railway networks using evolutionary multiobjective optimization: Case study line Braşov Abstract--In this paper, we propose a methodology based on signal processing and evolutionary multiobjective optimization to facilitate the maintenance decision making of infra-managers in regional railways. Using a train in operation (with passengers onboard), we capture the condition of the rails using Axle Box Acceleration measurements. Then, using Hilbert-Huang Transform, the locations where the major risks are detected and assessed with a degradation model. Finally, evolutionary multiobjective optimization is employed to solve the maintenance decision problem, and to facilitate the visualization of the trade-offs between number of interventions and performance. Real-life measurements from the track from Bra ov to Z rne ti in Romania are included to show the methodology.

Design, Development and Field Trial Evaluation of An intelligent Asset Management System For Railway Networks

“…In addition to GPR, the remaining useful life of the track may be also determined using the Hilbert -Huang entropy using horizontal vibration signals [47]. The Hilbert-Huang Transform has been adopted in [48] to detect track irregularities. The Hilbert Spectrum is obtained by combining empirical mode decomposition (EMD) with the Hilbert transform, namely, the HHT.…”

Rail Break Prediction and Cause Analysis Using Imbalanced In-Service Train Data

“…The magnitude of the in-service train data is influenced by train speed, as the sensors are installed on the axle boxes of the in-service train's bogies. In normal running, the higher the speed, the higher the dynamic responses such as vertical acceleration [44]. To consider this effect, the train speed is collected as one of the parameters.…”