Digital Image Correlation (DIC) has been established as a flexible and effective technique to measure the displacements on specimen surface by matching the reference subsets in the undeformed image with the target subsets in the deformed image. With the existing DIC techniques, the user must rely on experience and intuition to manually define the size of the reference subset, which is found to be critical to the accuracy of measured displacements. In this paper, the problem of subset size selection in the DIC technique is investigated. Based on the Sum of Squared Differences (SSD) correlation criterion as well as the assumption that the gray intensity gradients of image noise are much lower than that of speckle image, a theoretical model of the displacement measurement accuracy of DIC is derived. The theoretical model indicates that the displacement measurement accuracy of DIC can be accurately predicted based on the variance of image noise and Sum of Square of Subset Intensity Gradients (SSSIG). The model further leads to a simple criterion for choosing a proper subset size for the DIC analysis. Numerical experiments have been performed to validate the proposed concepts, and the calculated results show good agreements with the theoretical predictions.

By using the principle of stereovision, 3D digital image correlation (3D-DIC) can determine the 3D morphology and deformation of a target and has been widely used in experimental mechanics as a noncontact 3D measurement technique. To eliminate the limitations of the conventional 3D-DIC system, this study proposes a calibration-free single-lens 3D-DIC system based on a bilateral telecentric lens and a bi-prism. The performance of the proposed system is verified by tests of rigid-body translation along the out-of-plane direction. As a comparison, the same rigid-body translations are measured using a single-entocentric-lens 3D-DIC system. The results show that the measurement accuracy of the proposed system is higher than that of the entocentric-lens-based one. As an application, the proposed system is used to measure the thermal linear expansion of a ceramic plate at elevated temperatures. The reasonable measurement results verify its applicability in deformation measurements, even in high-temperature environments.

Three-dimensional (3D) digital image correlation (DIC) is one of the most popular techniques used in engineering for strain and deformation measurement. However, the error analysis of 3D DIC, especially which kind of parameters dominates the error of 3D coordinate reconstruction in any kind of configuration, is still under study. In this paper, a technique that can be used for error determination of reconstruction is presented. The influence from the system calibration and image correlation to the error is theoretically analyzed. From numerical experiments of one-dimensional line and two-dimensional plane, the evaluation procedure is validated to be flexible. A typical test with standard objects is also conducted. With this technique, once a 3D DIC system is set up and images of objects with speckles and calibration boards are recorded, the error of the configuration can be immediately evaluated. The standard deviation of every point in the world coordinate can be determined by statistical analysis.

The three-dimensional digital image correlation (3D-DIC) method is rapidly developing and is being widely applied to engineering and manufacturing. Despite its extensive use, the error caused by different image matching algorithms is seldom discussed. An algorithm for 3D speckle image generation is proposed, and the performances of different subpixel correlation algorithms are studied. The advantage is that there is no interpolation bias of texture in the simulation before and after deformation, and the error from the interpolation of speckle can be omitted in this algorithm. An error criterion for 3D reconstruction is proposed. 3D speckle images were simulated, and the performance of four subpixel algorithms is addressed. Based on the research results of different subpixel algorithms, a first-order Newton–Raphson iteration method and gradient-based method are recommended for 3D-DIC measurement.

A 3D SEM Moiré Method (SMM) is proposed in this investigation for the first time for 3D shape measurement with nano-scale sensitivity. The geometric model of the 3D SMM has been theoretically established, combining the stereovision technology in an SEM with the existing principles of in-plane SMM. The Virtual Projection Fringe (VPF) generated under different conditions has been analyzed for 3D reconstructions. Two typical applications have been used to experimentally validate the theoretical model. Experimental results, with the height measurement sensitivity less than 10nm, agree well with the theoretical model we proposed. The uncertainty analysis for the method has also been performed by other auxiliary measurements.