A method for in-field railhead crack detection using digital image correlation
Journal article, 2022

Railway infrastructure managers must decide when and how to maintain rails. However, they often have insufficient information about railhead cracks. Therefore, we propose a new method for rail crack detection using a train-mounted digital image correlation (DIC) camera system. The measurement train's weight cause rail bending, allowing the DIC to measure strain concentrations caused by surface-breaking cracks. In this study, we evaluate the method under laboratory conditions. The detected cracks correlate to the actual crack network in the analysed rail field sample. Furthermore, finite element simulations show the method's high sensitivity to crack depths. Existing methods, such as ultra-sonic and eddy-current, produce damage severity indications. The proposed method complements these techniques by providing a discrete description of the surface-breaking cracks and their depth. This information enables infrastructure managers to optimize rail maintenance. Additionally, such detailed measurements can be valuable for research in railhead damage evolution.


railway maintenance

crack detection

digital image correlation

Conditioning monitoring


Knut Andreas Meyer

Chalmers, Industrial and Materials Science, Material and Computational Mechanics

Daniel Gren

Chalmers, Industrial and Materials Science, Engineering Materials

Johan Ahlström

Chalmers, Industrial and Materials Science, Engineering Materials

Anders Ekberg

Chalmers, Mechanics and Maritime Sciences (M2), Dynamics

International Journal of Rail Transportation

2324-8378 (ISSN) 2324-8386 (eISSN)

Vol. 10 6 675-694

Influence of anisotropy on deterioration of rail materials (CHARMEC MU34)

Chalmers Railway Mechanics (CHARMEC), 2015-05-18 -- 2020-05-15.

European Commission (EC), 2015-05-18 -- 2020-05-15.

Research into enhanced tracks, switches and structures (In2Track)

European Commission (EC) (EC/H2020/730841), 2016-12-01 -- 2020-12-31.

Swedish Transport Administration (TRV2016/50535), 2016-09-01 -- 2019-06-30.

Research into enhanced track and switch and crossing system 2 (In2Track-2)

European Commission (EC) (EC/H2020/826255), 2018-11-01 -- 2021-10-31.

Swedish Transport Administration, 2018-11-01 -- 2021-10-31.

Subject Categories

Applied Mechanics

Medical Laboratory and Measurements Technologies

Other Medical Engineering

Computer Vision and Robotics (Autonomous Systems)



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