1. A Robot-Assisted Microscopy System for Digital Image Correlation in Fatigue Crack Growth Testing
- Author
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Paysan, Florian, Dietrich, Eric, and Breitbarth, Eric
- Subjects
Microscopy ,Mechanics of Materials ,Digital Image Correlation ,Mechanical Engineering ,Moveable camera system ,Aerospace Engineering ,Robotics ,Fatigue crack growth - Abstract
Background Digital image correlation (DIC) with microscopes has become an important experimental tool in fracture mechanics to study local effects such as the plastic zone, crack closure, crack deflection or crack branching. High-resolution light microscopes provide 2D images but the field of view is limited to a small area and very sensitive to its alignment. A flexible positioning system is therefore needed to collect such DIC data during the entire fatigue crack growth process. Objective We present in our paper a new experimental setup for local high-resolution 2D DIC measurements at any location and at any time during fatigue crack growth experiments with a non-fixed DIC microscopy system. Methods We use a robot to move the 2D DIC microscope to any location on the surface of the specimen. Optical and tactile methods automatically adjust the system and ensure highest image quality as well as accurate alignment. In addition, an advanced repositioning method reduces out-of-plane motion effects. Results The robot is able to achieve a repositioning accuracy of less than 0.06 mm in vector space, resulting in very low Von Mises strain scattering of 0.07 to 0.09% in the DIC evaluation. The system minimizes systematic errors caused by translation and rotational deviations. Effects such as crack deflection, crack branching or the plastic zone of a fatigue crack can be investigated with a field of view of 10.2 x 6.4 mm2. Conclusions The robot supported DIC system generates up to 8000 high-quality DIC images in an experiment that enables the application of digital evaluation algorithms. Redundant information create confidence in the results as all revealed effects are comprehensible. This increases the information content of a single fatigue crack growth test and accelerates knowledge generation.
- Published
- 2023