Investigation of Track Geometry Defects on a Heavy-Haul Railway Line
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 147, Issue 9
Abstract
This paper presents an in-depth case study of a heavy-haul railway line in Sweden to analyze the twist and longitudinal level geometry defects. A linear model was applied to model the evolution of the amplitude of the longitudinal level defects and twist over time. Despite the effect of the defect shapes on the dynamic track loads, the amplitude of the defects still is the only criterion used for the assessment of geometry defect severity. The application of first- and second-order derivatives to capture information about the shape of defects was investigated in the case study. In addition, the RUSBoost algorithm was used to classify track sections into healthy and unhealthy sections using the imbalance class data set. In this algorithm, the standard deviation and the kurtosis of the geometry parameters were used as explanatory variables. Finally, the abnormal track geometry degradation patterns identified in the case study were explored in detail. The results of the analysis can be used directly in maintenance modeling and used for the purpose of maintenance scheduling.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may be provided only with restrictions. The track geometry data were provided by Trafikverket and require permission for distribution.
Acknowledgments
The authors thank the Swedish Transport Administration (Trafikverket), Luleå Railway Research Center (JVTC) and Bana Väg För Framtiden (BVFF) for their technical and financial support provided during this project. Specific thanks are extended to the SIMTRACK project partners for their continuous technical and professional support and sharing of their expertise.
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© 2021 American Society of Civil Engineers.
History
Received: Feb 18, 2021
Accepted: Apr 26, 2021
Published online: Jun 29, 2021
Published in print: Sep 1, 2021
Discussion open until: Nov 29, 2021
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