As a practical and effective tool for quantitative in-plane deformation measurement of a planar object surface, two-dimensional digital image correlation (2D DIC) is now widely accepted and commonly used in the field of experimental mechanics. It directly provides full-field displacements to sub-pixel accuracy and full-field strains by comparing the digital images of a test object surface acquired before and after deformation. In this review, methodologies of the 2D DIC technique for displacement field measurement and strain field estimation are systematically reviewed and discussed. Detailed analyses of the measurement accuracy considering the influences of both experimental conditions and algorithm details are provided. Measures for achieving high accuracy deformation measurement using the 2D DIC technique are also recommended. Since microscale and nanoscale deformation measurement can easily be realized by combining the 2D DIC technique with high-spatial-resolution microscopes, the 2D DIC technique should find more applications in broad areas.

https://iopscience.iop.org/article/10.1088/0957-0233/20/6/062001/pdf

Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review

Developments in digital image correlation in the last two decades have made it a popular and effective tool for full-field displacement and strain measurements in experimental mechanics In digital image correlation, the use of the sub-pixel registration algorithm is regarded as the key technique to improve accuracy Different types of sub-pixel registration algorithms have been developed However, little quantitative research has been carried out to compare their performances This paper investigates three types of the most commonly used sub-pixel displacement registration algorithms in terms of the registration accuracy and the computational efficiency using computer-simulated speckle images A detailed examination of the performances of each algorithm reveals that the iterative spatial domain cross-correlation algorithm (Newton–Raphson method) is more accurate, but much slower than other algorithms, and is recommended for use in these applications

https://iopscience.iop.org/article/10.1088/0957-0233/17/6/045/pdf

Performance of sub-pixel registration algorithms in digital image correlation

As a carrier of deformation information, the speckle pattern, or more exactly the random intensity distributions, which could be naturally occurred or artificially fabricated onto test samples’ surface, plays an indispensable role in digital image correlation (DIC). It is now well recognized that the accuracy and precision in DIC measurements not only rely on correlation algorithms, but also depend highly on the quality of the speckle pattern. Considering the huge diversity in test materials, spatial scales and experimental conditions, speckle pattern fabrication could be a challenging issue facing DIC practitioners. To obtain good speckle patterns suitable for DIC measurements, some key issues of fabrication methods and quality assessment of speckle patterns must be well addressed. To this end, this review systematically presents the speckle pattern classification and fabrication techniques for various samples and scales, as well as some typical quality assessment metrics.

A Review of Speckle Pattern Fabrication and Assessment for Digital Image Correlation

Speckle pattern quality assessment for digital image correlation

Use of rigid-body motion for the investigation and estimation of the measurement errors related to digital image correlation technique

This paper presents a "fast and simple" (FAS) detection algorithm based on the digital image correlation for measurement of the surface deformation of planar objects. The proposed algorithm uses only fine search at the pixel level resolution and surface fitting for sub-pixel level. Two different specimens are investigated to explore the feasibility of this proposed algorithm. The displacements calculated by the FAS algorithm are compared with the ones obtained from Newton-Raphson method (N-R) and Enhanced Sequential Similarity Detection Algorithm (ESSDA). The results show that the experimental data are in good agreement with the theoretical solution. The proposed algorithm is found to be much faster than Newton-Raphson method with inferior, yet reasonable, accuracy for displacement and strain evaluation in the cases of uniaxial tension and disk under diametrical compression tests.

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Po-Chih Hung

Papers

In-plane strain measurement by digital image correlation