Publications
A realistic error budget for two dimension digital image correlation
There has been a lot of interest in the matching error for two-dimensional digital image correlation (2D-DIC), including the matching bias and variance; however, there are a number of other sources of error that must also be considered. These include temperature drift of the camera, out-of-plane sample motion, lack of perpendicularity, under-matched subset shape functions, and filtering of the results during the strain calculation. This talk will use experimental evidence to demonstrate some of the ignored error sources and compile a complete “notional” error budget for a typical 2D measurement.