Influencing factors for condition-based maintenance in railway tracks using knowledge-based approach

Influencing factors for condition-based maintenance in railway tracks using knowledge-based approach

Jamshidi, A. (TU Delft Railway Engineering)
Hajizadeh, S. (TU Delft Railway Engineering)
Naeimi, M. (TU Delft Railway Engineering)
Nunez, Alfredo (TU Delft Railway Engineering)
Li, Z. (TU Delft Railway Engineering)

2017

In this paper, we present a condition-based maintenance decision method using
knowledge-based approach for rail surface defects. A railway track may contain a considerable number of surface defects which influence track maintenance decisions. The proposed method is based on two sets of maintenance decision factors i.e. (1) defect detection data and (2) prior knowledge of the track. A defect detection model is proposed to monitor surface defects of the track
including squats. The detection model relies on track images and Axle Box Acceleration (ABA) signals to give both positions of severity and defects. To acquire the prior knowledge, a set of track monitoring data is selected. A fuzzy inference model is proposed relying on the maintenance factors
to give the track health condition in a case study of the Dutch railway network. The proposed condition-based maintenance model enables infrastructure manager to prioritize critical pieces of the track based on the health condition.

Condition-based maintenance decision
Rail surface defects
Bayesian model

http://resolver.tudelft.nl/uuid:754027da-0ca8-4064-b312-1cd3ce99da19

Proceedings of the First International Conference on Rail Transportation: ICRT2017

1st International Conference on Rail Transportation, 2017-07-10 → 2017-07-12, Chengdu, China

Institutional Repository

conference paper

© 2017 A. Jamshidi, S. Hajizadeh, M. Naeimi, Alfredo Nunez, Z. Li