A method for in-field railhead crack detection using digital image correlation

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 train-mounted digital image correlation (DIC) camera system. The measurement train’s weight cause bending, allowing the DIC measure strain concentrations caused by surface-breaking In this study, evaluate under laboratory conditions. detected cracks correlate actual network in analysed field sample. Furthermore, finite element simulations show method’s high sensitivity depths. Existing methods, such as ultra-sonic eddy-current, produce damage severity indications. proposed complements these techniques providing discrete description of their depth. This enables optimize maintenance. Additionally, detailed measurements can be valuable research evolution.