The application of digital image correlation (DIC) in fatigue experimentation: A review

Abstract

In recent years, the use of digital image correlation (DIC) in fatigue experiments has become widespread. It is estimated that ~1000 published works exist that outline fatigue experiments in which DIC is employed for displacement and strain measurement. Of these, ~900 were published in the last 10 years. DIC is a noncontact method that uses a series of digital images to calculate full‐field strains on the surface of an object, planer or curved. Typical commercial DIC systems compute strains at resolutions high enough to trace hysteresis loops in metals. Properly operated open‐source systems can do the same. The DIC method is applied not only on optically based digital images but also on digital images from ultra‐high resolution (ultra‐HR) microscopes like a scanning electron microscope (SEM) or on volumetric images from computed tomography (CT) scans. In fatigue analysis, DIC provides much more information than that of an extensometer. Full‐field strains from DIC can be acquired at different scales (i.e., microscale, macroscale, and nanoscale) and can be related to items such as microstructural features, interacting surfaces (e.g., fretting), fatigue crack growth phenomenon, and distinct forms of energy. Because fatigue is a highly complex, strain‐induced process, the DIC method is and will be an important tool for current and future research in fatigue. This review begins with an overview of the history and fundamentals of DIC including an evaluation of the overall performance and accuracy of the method. Publications selected for review are then presented and discussed. Remarks about the present state‐of‐the‐art and an outlook for future work to be done are then provided.

Next generation fatigue crack growth experiments of aerospace materials

“…Overall, literature shows that the integration of experimental DIC (especially HRDIC) and algorithmic analyses yields deep understanding of crack growth behaviour and its underlying mechanisms 40 . However, this approach requires entirely new test infrastructures, including interconnected hardware, i.e.…”

“…As a consequence, for fracture mechanics, digital image correlation (DIC) has become a state-of-the-art method for generating full-field information of displacements and strains during crack growth experiments . For instance, DIC has been successfully applied together with numerical or analytical approaches to calculate the J-integral, stress intensity factors or T-stress 20,23,[25][26][27]29,[31][32][33][34][37][38][39][40][41] , analyse the crack tip plastic zone 21,22 , crack opening displacements 36,37 , or mechanisms acting locally at the crack tip, such as strain accumulation 24 . However, the non-automated acquisition and analysis of DIC data is not readily scalable in terms of time and the amount of information that can be processed.…”

Research on monitoring method for crack depth of railway hollow axle during bench test

“…And the crack length is monitored during the test. Common monitoring methods of crack length include plastic replica method, magnetic particle inspection method, images captured by means of optical microscope, 23 and DIC testing technology 43 . However, cracks are usually described using crack depth, and how to monitor crack depth variation has been a challenge for fatigue test of full‐scale axles.…”

Application of high‐performance DIC for a comprehensive evaluation of biaxial fatigue crack growth experiments

“…Alternatively, methods like crack opening displacement (COD) or J‐integral have been developed for a direct assessment of from full‐field DIC. [ 6,7 ] However, under mixed‐mode conditions, they are still under research. [ 8 ] All these methods require clear recognition of the crack tip itself.…”