Core concepts and considerations for accurate DIC measurements. Topics include selecting appropriate subset sizes, step sizes, and strain filters; understanding projection error and strain tensor formulations; avoiding pitfalls when averaging angular data; validating DIC results against strain gauges; and optimizing hardware setup through proper lens selection and stereo angle configuration.
Overview Many high-speed cameras allow speed increases by reducing (cropping) image resolution. However, calibration can be difficult or impossible at the reduced resolution; in most cases calibrating...
Because of how we track and match images in order to obtain data, and because of the fundamentals of strain theory, we must treat the area of interest as a continuous surface. Discontinuous surfaces ...
Some of the most useful results in Digital Image Correlation come from high-magnification, small field of view tests. At the same time, these tests can be increasingly difficult, depending on the magn...
Sometimes, images acquired for use in 2D or 3D digital image correlation tests can be too dark; noisy; blurry; or aliased. From time to time we are asked whether it would be beneficial to process thes...
Using DIC (digital image correlation) to measure cracking surfaces or breaking specimens can be a difficult task. The attached application note discusses some realities that must be considered when us...
In Vic-2D and Vic-3D, some of the inspector tools will cause data to be averaged over a certain area - specifically, the Disc and Rectangle tools. With these tools, when the data is extracted, the res...
The link application note discusses the realities to consider when using DIC to measure a specimen with surface cracking, and how shape, displacement, and strain measurments may be affected when surfa...
General introduction to DIC and theory presentation can be downloaded from the link below with embedded media; Presentation Download Link...
In analysis, edge data can seem to be missing. This is due to analysis parameters and calculation methods. We have one data point for every subset. We report the data in the center of the subset. For ...