Regularized Newton-Raphson method for small strain calculation

Digital Image Correlation (DIC) has been proven to be a highly reliable framework for the full-field displacement and strain measurement of materials that undergo deformation when subjected to physical stresses. This paper presents a new method that extends the popular Newton-Raphson algorithm through the inclusion of spatial regularization in the minimization process used to obtain the motion data. The basic principle is that the motion data is calculated between corresponding blocks in the reference and deformed images using adaptively previously obtained motion estimates in the immediate vicinity of the respective location along with the local block-based image information. The results indicate significant accuracy improvements over the classic approach especially when the block sizes and strain calculation windows used for motion and strain estimation decrease in size

Study of image characteristics on digital image correlation error assessment

In this paper, errors related to digital image correlation (DIC) technique applied to measurements of displacements are estimated. This work is based on the generation of synthetic images representative of real speckle patterns. With these images, various parameters are treated in order to determine their impact on the measurement error. These parameters are related to the type of deformation imposed on the speckle, the speckle itself (encoding of the image, image saturation) or the software (subset size)

Determination of high temperature strains using a PC based vision system

With the widespread availability of video digitizers and cheap personal computers, the use of computer vision as an experimental tool is becoming common place. These systems are being used to make a wide variety of measurements that range from simple surface characterization to velocity profiles. The Sub-Pixel Digital Image Correlation technique has been developed to measure full field displacement and gradients of the surface of an object subjected to a driving force. The technique has shown its utility by measuring the deformation and movement of objects that range from simple translation to fluid velocity profiles to crack tip deformation of solid rocket fuel. This technique has recently been improved and used to measure the surface displacement field of an object at high temperature. The development of a PC based Sub-Pixel Digital Image Correlation system has yielded an accurate and easy to use system for measuring surface displacements and gradients. Experiments have been performed to show the system is viable for measuring thermal strain

Some experimental observations of crack-tip mechanics with displacement data

Estudio de la mecánica en el vértice de la grieta mediante datos de desplazamiento.In the past two decades, crack-tip mechanics has been increasingly studied with full-field techniques. Within these techniques, Digital Image Correlation (DIC) has been most widely used due to its many advantages, to extract important crack-tip information, including Stress Intensity Factor (SIF), Crack Opening Displacement, J-integral, T-stress, closure level, plastic zone size, etc. However, little information is given in the literature about the experimental setup that provides best estimations for the different parameters. The current work aims at understanding how the experimental conditions used in DIC influence the crack-tip information extracted experimentally. The influence of parameters such as magnification factor, size of the images, position of the images with respect the crack-tip and size of the subset used in the correlation is studied. The influence is studied in terms of SIF and T-stress by using Williams’ model. The concept of determination of the K-dominance zone from experimental data has also explored. In this regard, cyclic loading on a fatigue crack in a compact tension (CT) specimen, made of aluminium 2024-T351 alloy, has been applied and the surface deformation ahead of the crack tip has been examined. The comparison between theoretical and experimental values of KI showed that the effect of subset size on the measured KI is negligible compared to the effect of size of the image.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Dense and accurate motion and strain estimation in high resolution speckle images using an image-adaptive approach

Digital image processing methods represent a viable and well acknowledged alternative to strain gauges and interferometric techniques for determining full-field displacements and strains in materials under stress. This paper presents an image adaptive technique for dense motion and strain estimation using high-resolution speckle images that show the analyzed material in its original and deformed states. The algorithm starts by dividing the speckle image showing the original state into irregular cells taking into consideration both spatial and gradient image information present. Subsequently the Newton-Raphson digital image correlation technique is applied to calculate the corresponding motion for each cell. Adaptive spatial regularization in the form of the Geman-McClure robust spatial estimator is employed to increase the spatial consistency of the motion components of a cell with respect to the components of neighbouring cells. To obtain the final strain information, local least-squares fitting using a linear displacement model is performed on the horizontal and vertical displacement fields. To evaluate the presented image partitioning and strain estimation techniques two numerical and two real experiments are employed. The numerical experiments simulate the deformation of a specimen with constant strain across the surface as well as small rigid-body rotations present while real experiments consist specimens that undergo uniaxial stress. The results indicate very good accuracy of the recovered strains as well as better rotation insensitivity compared to classical techniques

Submicron Deformation Field Measurements II: Improved Digital Image Correlation

This is the second paper in a series of three devoted to the applicaiton of Scanning Tunneling Microscopy to mechanics problems. In this paper improvements to the Digital Image Correlation method are outlined, a technique that compares digital images of a specimen surface before and after deformation to deduce its (2-D) surface displacement field and strains. The necessity of using the framework of large deformation theory for accurately addressing rigid body rotations to reduce associated errors in the strain components is pointed out. In addition, the algorithm is extended to compute the three-dimensional surface displacement field from Scanning Tunneling Microscope data; also, significant improvements are achieved in the rate as well as the robustness of the convergence. For Scanning Tunneling Microscopy topographs the resolution yields 4.8 nm for the in-plane and 1.5 nm for the out-of-plane displacement components spanning an area of 10 μm x 10 μm

Dense and accurate motion and strain estimation in high resolution speckle images using an image-adaptive approach

Digital image processing methods represent a viable and well acknowledged alternative to strain gauges and interferometric techniques for determining full-field displacements and strains in materials under stress. This paper presents an image adaptive technique for dense motion and strain estimation using high-resolution speckle images that show the analyzed material in its original and deformed states. The algorithm starts by dividing the speckle image showing the original state into irregular cells taking into consideration both spatial and gradient image information present. Subsequently the Newton-Raphson digital image correlation technique is applied to calculate the corresponding motion for each cell. Adaptive spatial regularization in the form of the Geman-McClure robust spatial estimator is employed to increase the spatial consistency of the motion components of a cell with respect to the components of neighbouring cells. To obtain the final strain information, local least-squares fitting using a linear displacement model is performed on the horizontal and vertical displacement fields. To evaluate the presented image partitioning and strain estimation techniques two numerical and two real experiments are employed. The numerical experiments simulate the deformation of a specimen with constant strain across the surface as well as small rigid-body rotations present while real experiments consist specimens that undergo uniaxial stress. The results indicate very good accuracy of the recovered strains as well as better rotation insensitivity compared to classical techniques

On the Use of Digital Image Correlation to Analyze the Mechanical Properties of Brittle Matrix Composites

The 2D digital image correlation technique needs a single CCD camera to acquire the surface patterns of a region of a specimen in the undeformed and deformed states. With two images, one can determine in-plane displacement and strain fields. Its performance is assessed and discussed in real experimental situations. Thanks to its sub-pixel resolution, it can be used to monitor experiments even for brittle and quasi-brittle materials, namely materials for which the strain levels remain low (less than 0.1% in many cases). Two examples are given. Firstly, elastic properties of BraSiC (a silicon-based braze to assemble SiC/SiC composites) are extracted from kinematic fields estimated by utilizing a digital image correlation method. Secondly, the technique is utilized to analyze experimental results of a plane shear experiment and validate a damage model describing different degradations in a C/C composite material