Topic
Digital image correlation
About: Digital image correlation is a research topic. Over the lifetime, 7842 publications have been published within this topic receiving 132166 citations.
Papers published on a yearly basis
Papers
More filters
TL;DR: A general presentation of the extraction of displacement fields from the knowledge of pictures taken at different instants of an experiment is given, and different strategies can be followed to achieve a sub-pixel uncertainty.
Abstract: The current development of digital image correlation, whose displacement uncertainty is well below the pixel value, enables one to better characterise the behaviour of materials and the response of structures to external loads. A general presentation of the extraction of displacement fields from the knowledge of pictures taken at different instants of an experiment is given. Different strategies can be followed to achieve a sub-pixel uncertainty. From these measurements, new identification procedures are devised making use of full-field measures. A priori or a posteriori routes can be followed. They are illustrated on the analysis of a Brazilian test.
764 citations
TL;DR: In this article, a three-dimensional extension of two-dimensional digital image correlation is developed using digital image volumes generated through high-resolution X-ray tomography of samples with microarchitectural detail, such as the trabecular bone tissue found within the skeleton.
Abstract: A three-dimensional extension of two-dimensional digital image correlation has been developed. The technique uses digital image volumes generated through high-resolution X-ray tomography of samples with microarchitectural detail, such as the trabecular bone tissue found within the skeleton. Image texture within the material is used for displacement field measurement by subvolume tracking. Strain fields are calculated from the displacement fields by gradient estimation techniques. Estimates of measurement precision were developed through correlation of repeat unloaded data sets for a simple sum-of-squares displacement-only correlation formulation. Displacement vector component errors were normally distributed, with a standard deviation of 0.035 voxels (1.22 μm). Strain tensor component errors were also normally distributed, with a standard deviation of approximately 0.0003. The method was applied to two samples taken from the thigh bone near the knee. Strains were effectively measured in both the elastic and postyield regimes of material behavior, and the spatial patterns showed clear relationships to the sample microarchitectures.
723 citations
TL;DR: In this article, a new methodology is proposed to estimate displacement fields from pairs of images (reference and strained) that evaluates continuous displacement fields, specialized to a finite-element decomposition.
Abstract: A new methodology is proposed to estimate displacement fields from pairs of images (reference and strained) that evaluates continuous displacement fields. This approach is specialized to a finite-element decomposition, therefore providing a natural interface with a numerical modeling of the mechanical behavior used for identification purposes. The method is illustrated with the analysis of Portevin–Le Châtelier bands in an aluminum alloy sample subjected to a tensile test. A significant progress with respect to classical digital image correlation techniques is observed in terms of spatial resolution and uncertainty.
654 citations
TL;DR: It is shown that the position-dependent bias in a numerical study can lead to apparent strains of the order of 40% of the actual strain level, and methods are presented to reduce this bias to acceptable levels.
Abstract: Recently, digital image correlation as a tool for surface defor- mation measurements has found widespread use and acceptance in the field of experimental mechanics. The method is known to reconstruct displacements with subpixel accuracy that depends on various factors such as image quality, noise, and the correlation algorithm chosen. How- ever, the systematic errors of the method have not been studied in detail. We address the systematic errors of the iterative spatial domain cross- correlation algorithm caused by gray-value interpolation. We investigate the position-dependent bias in a numerical study and show that it can lead to apparent strains of the order of 40% of the actual strain level. Furthermore, we present methods to reduce this bias to acceptable lev- els. © 2000 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(00)00911-9)
602 citations
TL;DR: In this article, the effect of out-of-plane motion on 2D and 3D digital image correlation measurements is demonstrated using basic theoretical pinhole image equations and experimentally through synchronized, multi-system measurements.
588 citations