A Study of the Influence of Calibration Uncertainty on the Global Uncertainty for Digital Image Correlation Using a Monte Carlo Approach

Stereo digital image correlation (DIC) is now a standard measurement technique. It is, therefore, important to quantify the measurement uncertainties when using it for experiments. Because of the complexity of the DIC measurement process, a Monte Carlo approach is presented as a method to discover the magnitude of the stereo-DIC calibration uncertainty. Then, the calibration errors, along with an assumed sensor position error, are propagated through the stereo-triangulation process to find the uncertainty in three-dimensional position and object motion. Details on the statistical results of the calibration parameters are presented, with estimated errors for different calibration targets and calibration image quality. A sensitivity study was done to look at the influence of the different calibration error sources. Details on the best approach for propagating the errors from a statistical perspective are discussed, including the importance of using a boot-strap approach for error propagation because of the covariance of many of the calibration parameters. The calibration and error propagation results are then interpreted to provide some best-practices guidelines for DIC.