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Ji et al. Intell Robot 2021;1(2):151-75 Intelligence & Robotics
DOI: 10.20517/ir.2021.14

Review Open Access

Rail track condition monitoring: a review on deep

learning approaches

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1
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Albert Ji , Wai Lok Woo , Eugene Wai Leong Wong , Yang Thee Quek 3
1
NewRIIS, Newcastle University, Singapore 609607, Singapore.
2
Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK.
3
School of Engineering, Republic Polytechnic Singapore, Singapore 738964, Singapore.
Correspondence to: Prof. Wai Lok Woo, Department of Computer and Information Sciences, Northumbria University, Ellison
Place, Newcastle upon Tyne NE1 8ST, UK. E-mail: wailok.woo@northumbria.ac.uk
How to cite this article: Ji A, Woo WL, Wong EWL, Quek YT. Rail track condition monitoring: a review on deep learning
approaches. Intell Robot 2021;1(2):151-75. https://dx.doi.org/10.20517/ir.2021.14
Received: 21 Oct 2021 First Decision: 23 Nov 2021 Revised: 12 Dec 2021 Accepted: 29 Dec 2021 Published: 31 Dec 2021

Academic Editors: Simon X. Yang, Xin Xu Copy Editor: Xi-Jun Chen Production Editor: Xi-Jun Chen

Abstract
Rail track is a critical component of rail systems. Accidents or interruptions caused by rail track anomalies usually
possess severe outcomes. Therefore, rail track condition monitoring is an important task. Over the past decade,
deep learning techniques have been rapidly developed and deployed. In the paper, we review the existing literature
on applying deep learning to rail track condition monitoring. Potential challenges and opportunities are discussed
for the research community to decide on possible directions. Two application cases are presented to illustrate the
implementation of deep learning to rail track condition monitoring in practice before we conclude the paper.

Keywords: Rail track maintenance, condition monitoring, anomaly detection and classification, deep learning

1. INTRODUCTION
The rail industry plays an important role in a nation’s economy and development and directly affects the
lifestyle of the residents. Hence, there is a low tolerance level by the public to any accidents or negative
events happening to the rail operations as the economy, the livelihood, and the country’s reputation would
be brought down and the social and political risk level will rise. The rail systems around the world operate
under different environments with their most critical infrastructure, the steel rail track, including rails,
sleepers, ballast, fastener, and subgrade. Undesirable consequences such as derailment, death, injury,

© The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0
International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing,
adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as
long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and
indicate if changes were made.

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