Digital Image Correlation (DIC) is a commonly used method in measuring full-field localized displacement and deformation on a surface. DIC is adaptable for a variety of length scales, and micro- to nano-scale DIC measurements have been previously achieved using techniques including microscopy and high-magnification lenses. At such high magnifications, image stitching has been used to achieve high-resolution imaging while allowing larger fields of view, but these methods have limitations when a long working distance is required, such as in-situ testing in an environmental chamber. As an alternative to image stitching, Super Resolution (SR) imaging combines multiple overlapping low resolution (LR) images of a common field of view into a single high resolution (HR) image without the need for as high of a magnification lens. Thus, SR can be performed at longer working distances for which high magnifications are unsuitable. This work compares the performance of three published SR imaging algorithms: Robust Super Resolution (RSR), Papoulis-Gerchberg (PG), and Structure-Adaptive Normalized Convolution (SANC). These three algorithms are applied in using DIC to obtain full-field displacements from a ring specimen. Due to the shape of the specimen, the field of view must be large enough to encompass the entire ring, which leaves relatively few pixels through the thickness of the ring. By applying the SR algorithms to the images of the ring, the number of pixels through the thickness can be effectively doubled. The ring is then monitored through two displacement tests. First, a rigid body displacement is applied to a specimen, after which a series of nine overlapping LR images are captured for each increment of displacement. Each set of LR images is then used to produce a single SR image for each algorithm. The images are then post-processed using DIC to compute full-field displacements. The applied rigid body displacement is then compared with the measured displacements from LR and SR images. Second, a mechanical test is performed in which a non-uniform strain field is produced in the specimen. The ring is loaded in tension by a pair of custom hook-shaped grips. A comparable procedure is followed in which the LR image sets are used to produce SR images of the deformed specimen. The LR and SR measurements produced from DIC are then compared with the measurements from a higher magnification image. It is found that the application of SR imaging in small-scale DIC improves spatial resolution, while offering improved precision and accuracy compared to the LR measurements.


Enhancing Micro-Scale Displacement Measurements Using Super Resolution Digital Image Correlation (Sr-DIC)

Division / Sponsors: 
Aerospace, Bioengineering, Applied Mechanics, Design Engineering Division, Advanced Energy Systems, Manufacturing Engineering Division, Noise Control and Acoustics, Nondestructive Evaluation, Diagnosis, and Prognosis (NDPD), Nuclear Engineering Division, Process Industries Division, Fluids Engineering, Heat Transfer, Materials, Microelectromechanical Systems, Safety Engineering and Risk Analysis, Computers & Information in Engineering


Paper Proceedings: https://asmedigitalcollection.asme.org/IMECE/IMECE2020/volume/84478

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