Digital Image Correlation

Abstract

In order to detect the occurrence of failure in a material, visual observation is a very intuitive approach. Although global failure is many times easier to observe visually, more dedicated analysis is required to detect small changes indicating the occurrence of first failure. One specific type of visual observation follows the idea to track and measure changes between subsequently acquired images of an object. The concept used for that purpose is based on digital image acquisition of a moving and deforming object and is known as digital image correlation (DIC). The background of this technique stems from the basic principles of optics, perspective imaging, and digital image analysis.The aim of this chapter is not to cover all aspects of the topic of DIC, but to introduce the key concepts and point out the relevant principles for measurement of strain fields of solid materials. For the interested reader, a comprehensive review on the topic is given by Sutton, Orteu, and Schreier [1] and a concise review on the application of 2D-DIC is also found in [2].One of the first attempts to use image correlation as a measurement technique to register features in images of different views was made by Hobrough in the 1950s. A few years later in 1961 he also developed a system to perform first quantitative positional measurements extracted from an image correlation process. With the availability of digitized images as provided by CMOS or CCD cameras in the 1960s and 1970s until the present days the branch of vision-based algorithms with a focus on DIC techniques has become a growing field of research. The development of the algorithms of the DIC method is driven by the accompanying applications in material science. Since the first experimental application in materials science by Peters and Ranson in 1982 [3], many experimental studies in the field of fiber reinforced composites were accompanied by DIC as a measurement technique [4][5][6][7][8][9][10][11][12]. In recent decades, suitable approaches have been developed to measure deformations with high magnification (e.g., inside a scanning electron microscope) and high-speed camera systems have been used to allow digital image correlation during high strain rate testing [13,14].

Open Guided Waves: online platform for ultrasonic guided wave measurements

“…To obtain the ν 23 Poisson’s ratio, the strain field was evaluated at the edge of the laminate (cf. approach presented in Sause 33 ).…”

Electrically Conductive Kevlar Fibers and Polymer-Matrix Composites Enabled by Atomic Layer Deposition

“…The tensile stage used was an Instron 4301 with a ±10 kN load cell (2525-804, Instron) and custom-made grips. The major principal strain (ε 1 ) in the sample was measured by 3D digital-image correlation (DIC), − using Vic-3D 7 software (Correlated Solutions, Inc.) and two machine-vision cameras (GRAS 50S5M-C, Point Gray) with 75 mm lenses (HF75SA-1, Fujinon) and 10 mm extension tubes (Figure S7). A speckle pattern was painted on the sample for DIC (Figure S8) by air-brushing black paint speckles (carbon black color, Golden, Inc.) over a white paint background (titanium white color, Golden, Inc.) …”

A Multiscale Study on Shale Wettability: Spontaneous Imbibition Versus Contact Angle

“…Its ability to estimate strains with reasonable accuracy has been well documented with experimental validation using strains measured by devices such as strain gauges (Gothekar, ; Rutkiewicz & Jakobczak, ; Sadek et al, ). In particular, DIC proved to be efficient in detecting microcracks in geomaterials (Kumar & Saride, ; Sause, ). Particularly, it was shown that for in‐plane and small‐strain measurements (such as in this study), DIC is very accurate (Acciaioli et al, ; Hoult et al, ).…”