Type A standard uncertainty evaluation in one measurement through uncertainty propagation from voxel values' distribution for computed tomography metrology

According to the guide to the expression of uncertainty in measurement, 'type A evaluation' generally requires repeated measurements, which are time-consuming for CT scans. To solve this problem, we developed a method for estimating the standard deviation of measurement results in one measurement through uncertainty propagation, which can be regarded as repeatability standard deviation to evaluate the type A standard uncertainty. The method first fits the CT voxel value distribution, uses the ISO50 method to determine the spatial distribution of surface points from the voxel value distribution and edge shape interpolation, and then derives the measurement results by fitting geometric parameters with the least square algorithm. Finally, the standard deviation of the measurement results is evaluated according to the distribution of the surface point position through uncertainty propagation. We performed simulations and experiments using the hole-plate with 28 holes to compare the uncertainty evaluated by our method and the type A standard uncertainty evaluated on the basis of a series of observations obtained under repeatability conditions. Both simulation and experimental results show that these two uncertainties follow the same statistical variation pattern. The Pearson correlation coefficients of the two uncertainties in simulation and experiment are 0.79 and 0.33, respectively, indicating that the uncertainty evaluated by the proposed method can directly replace the type A uncertainty or provide a reference similar to type A uncertainty for the evaluation of the combined uncertainty.