Title
Assessment of ballast layer under multiple field conditions in China
Author
Guo, Y. (TU Delft Railway Engineering)
Wang, Shilei (China Academy of Railway Sciences)
Jing, Guoqing (Beijing Jiaotong University)
Yang, Fei (China Academy of Railway Sciences)
Liu, Guixian (China Academy of Railway Sciences)
Qiang, Weile (China Academy of Railway Sciences)
Wang, Yan (China Academy of Railway Sciences)
Date
2022
Abstract
Ballast layer condition should be more regularly and accurately inspected to ensure safe train operation; however, traditional inspection methods cannot sufficiently fulfil this task. This paper presents a method of ground penetrating radar (GPR) application to reflect ballast layer fouling levels under diverse field conditions (annual gross passing load, cleaning and renewal year, fouling composition and transportation type). The results show that the GPR-based inspection method can assess the ballast layer fouling level with a 1–7% difference from the traditional sieving results. Fouling composition (especially metal materials) has a great effect on the GPR signals, thus affecting the inspection accuracy of ballast layer fouling level. Developing diverse GPR-based fouling indicators (by distinguishing different GPR signal features) can improve the GPR inspection applicability to the diverse field conditions.
Subject
Ballast fouling
GPR
Ground penetrating radar
Railway ballast
Track geometry
Track inspection
To reference this document use:
http://resolver.tudelft.nl/uuid:1307dc99-0c01-4a43-b182-500ec9367435
DOI
https://doi.org/10.1016/j.conbuildmat.2022.127740
Embargo date
2023-07-01
ISSN
0950-0618
Source
Construction and Building Materials, 340
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
journal article
Rights
© 2022 Y. Guo, Shilei Wang, Guoqing Jing, Fei Yang, Guixian Liu, Weile Qiang, Yan Wang