Developing and Extending Status Prediction Models for Railway Tracks Based on On-Board Monitoring Data
Open Access
- 30 January 2023
- journal article
- research article
- Published by SAGE Publications in Transportation Research Record: Journal of the Transportation Research Board
- Vol. 2677 (6), 708-719
- https://doi.org/10.1177/03611981221150245
Abstract
Assigning inspection trains to monitor track quality is a standard procedure for maintaining railway system safety. The main challenges lie in lacking time and resources to perform the inspections because of the increasing traffic nowadays. To overcome these challenges, many consider adopting the on-board monitoring (OBM) technique for performing the inspections. This technique assigns commercial trains, instead of traditional track recording vehicles (TRVs), to monitor the track status, allowing railway operators to perform more inspections without affecting the traffic and using expensive inspection trains as well. However, compared with TRV data, the new OBM data are of lower data quality and have fewer features, although they can be recorded more frequently. Therefore, new methods should be developed for effectively applying the new data. This study develops four models, namely the linear regression model, Markov model, ordinary Kriging model, and Kalman filter model, for predicting the track status based on the OBM data. Data collected from the Switzerland railway network are used for verifying the models. Results show that the proposed models can effectively predict the degradation of the track status in different ways and, therefore, assist railway operators in scheduling maintenance tasks.Keywords
This publication has 16 references indexed in Scilit:
- Fuzzy Approach in Rail Track Degradation PredictionJournal of Advanced Transportation, 2018
- Estimation and prediction of weather variables from surveillance data using spatio-temporal KrigingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- Evaluation of the effect of tamping on the track geometry condition: A case studyProceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 2016
- nullPhilosophy Study, 2016
- Establishment of Track Quality Index Standard Recommendations for Beijing MetroDiscrete Dynamics in Nature and Society, 2015
- Track quality prediction based on center approach Markov-Grey GM(1,1) modelPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- Modelling maintenance in railway infrastructure managementPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- A Bayesian model to assess rail track geometry degradation through its life-cycleResearch in Transportation Economics, 2012
- Modelling railway track geometry deteriorationProceedings of the Institution of Civil Engineers - Transport, 2011
- Reliability analysis and maintenance decision for railway sleepers using track condition informationJournal of the Operational Research Society, 2007