Accuracy Of Digital Image Correlation Research Articles

Assessing the influence of image capture frequency and asynchronicity on the accuracy of digital image correlation for fatigue analysis

Efficiency of Digital Image Correlation (DIC) technique for fatigue analysis can be significantly increased by capturing images at periodic intervals for correlation. However, the scarcity of images to capture the history of deformation can cause inaccuracies in full-field measurements. In this study, a comprehensive analysis is conducted to quantitatively assess this error by considering various scenarios. These include skipping of frames within every cycle and across cycles, as well as deviations between intended and captured frames. DIC measurements based on a high density of frames in every cycle is assumed to be true solution to evaluate error for all the cases. Analysis indicates that the skipping frames within every cycle introduces error in full-field strain, which increases with the propagation of crack. Interestingly, magnitude of error for periodic skipping of frames across cycles is observed to be more than skipping of frames within cycle. Furthermore, error shows an increasing trend as the gap between periodic frames becomes larger. Analysis also shows that random deviations disturbing periodicity of skipped frames for DIC can further increase the error in full-field strains. Overall, accuracy of the accelerated approach is seen to strongly depend on presence of discontinuous features and local gradients in response.

StrainNet-LD: Large Displacement digital image correlation based on deep learning and displacement-field decomposition

First, a displacement-field decomposition strategy is proposed that effectively enhances the accuracy of digital image correlation (DIC) algorithms under large displacement or deformation conditions. The implementation methodologies of displacement-field decomposition under both Lagrangian and Eulerian descriptions are derived and presented. Second, displacement-field decomposition is applied to speckle image correlation algorithms based on deep learning, resolving the contradiction between registration capability of large displacement and the accuracy. A CUDA-accelerated and residual learning-based strain fitting algorithm is proposed for high-precision and real-time strain computation. This method is named “StrainNet for Large Displacement” (StrainNet-LD). StrainNet-LD achieves a calculation speed of 768 × 768 × 6 fps (768 × 768 × 3 fps with strain calculated simultaneously) on GPU with displacement MAE < 0.05 pixels and strain MAE < 0.002ε. Finally, rubber tensile tests, 3D motion measurement of composite shells, and morphology reconstruction experiments of speckle-free composite repair structures are conducted to validate the algorithm's robustness and efficiency. Some vital discussions of displacement-field decomposition are given in the Appendixes. The code and dataset are available at https://github.com/GW-Wang-thu/StrainNet-LD.

Assessment of Digital Image Correlation Effectiveness and Quality in Determination of Surface Strains of Hybrid Steel/Composite Structures.

The application of the digital image correlation (DIC) contactless method has extended the possibilities of reliable assessment of structure strain fields and deformations throughout the last years. However, certain weak points in the analyses using the DIC method still exist. The fluctuations of the results caused by different factors as well as certain deficiencies in the evaluation of DIC accuracy in applications for hybrid steel/composite structures with adhesive joints are one of them. In the proposed paper, the assessment of DIC accuracy based on the range of strain fluctuation is proposed. This relies on the use of a polynomial approximation imposed on the results obtained from the DIC method. Such a proposal has been used for a certain correction of the DIC solution and has been verified by the introduction of different error measures. The evaluation of DIC possibilities and accuracy are presented on the examples of the static tensile tests of adhesively bonded steel/composite joints with three different adhesives applied. The obtained results clearly show that in a non-disturbed area, very good agreement between approximated DIC and FEM results is achieved. The relative average errors in an area, determined by comparison of DIC and FEM strains, are below 15%. It is also observed that the use of approximated strains by polynomial function leads to a more accurate solution with respect to FEM results. It is concluded that DIC can be successfully applied for the analyses of hybrid steel/adhesive/composite samples, such as determination of strain fields, non-contact visual detection of faults of manufacturing and their development and influence on the whole structure behavior during the strength tests, including the elastic response of materials.

An Exploration of Grain-Averaged Stress Measurement Using Partial Unloads with In situ Microscopic Image Correlation

BackgroundIn polycrystal mechanics, determination of stress is associated with diffraction methods that measure (the inherently-related) elastic strain. Microscopic digital image correlation (DIC), while commanding much higher intragranular resolution, measures total strain, and its local accuracy is typically insufficient to evaluate elastic strain magnitudes.ObjectiveIn situ DIC measurements over a partial unload of the polycrystal, where strains are virtually elastic, are explored for grain-averaged elastic strains and then, through a posed formalism, the stresses at the point of unload. Grain averaging is functionally employed to improve the DIC accuracy. The large objective is to emulate in situ complementary diffraction.MethodsNickel with high elastic anisotropy is chosen. The utilized highly-automated instrument offers maximal resolution for DIC with optical microscopy over a gross grain field. Orientations are predetermined for the same grain layer via electron backscatter diffraction. High-accuracy grain masks are produced to isolate the strain fields of individual grains.ResultsVery promising results are shown over a number of grains with sensible apparent compliance and stress values as well as linear unload behavior. Grains with sane results are largely predicted by a posed objectivity test that relies on DIC repeated with multiple reference loads.ConclusionThough it will require extremely careful implementations of microscopic DIC with high intragranular resolution, the premise of measuring intergranular stress fields via partial unloads seems to be viable and worthy of further exploration and verification. This capability that is superposed over strain measurement offers a more stringent validation of high-fidelity crystal plasticity models.

Uncertainty of digital image correlation under video compression and DSP optimization.

The storage and transmission of videos at high spatial resolution remain a great challenge in image-based optical techniques. The uncertainty of digital image correlation (DIC) was assessed following speckle video compression under High Efficiency Video Coding (HEVC/H.265). First, the evaluation criterion for the DIC accuracy affected by compression was provided. The stability of H.265 video compression in DIC was studied considering different compressed frames under different target quantization parameters (QPs) and compression ratios (CRs). The deformation uncertainty of the DIC itself as affected by H.265 video compression was further investigated through uniform translation and non-uniform sinusoidal deformation performance. Moreover, the optimized digital speckle pattern (DSP) was re-evaluated considering video compression-induced uncertainty. DSPs with parameters of different diameters and randomness were compressed using various QPs and CRs. In addition, DSP evaluation was performed under both translation and non-homogeneous deformation conditions. The feasibility of the re-optimized DSP under H.265 video compression was validated using a defective bending beam, and DSP videos with a speckle size of 8 pixels reached a high CR within an acceptable margin of error.

Method of generating speckle patterns for digital image correlation based on modified Conway's Game of Life.

The measurement accuracy of digital image correlation (DIC) is influenced by the quality of the speckle pattern. Although various models for generating random speckle patterns have been well discussed, obtaining appropriate speckle images with isotropic quality and performance could be a challenging issue in DIC. In this paper, we propose a novel (to our knowledge) method for generating speckle patterns based on modified Conway's game of life (GoL). By sequentially assembling the speckle patterns generated from the modified GoL, we produced the GoL speckle image. Then, verification and comparison experiments were conducted through pure in-plane translations. The results show that the generated speckle image which was resized with k s=6& k r=2 processing and subsequently fuzzified using a Gaussian filter, produces the best accuracy for DIC measurement. Furthermore, based on the rigid body in-plane rotation displacement tests in the physical experimental results of three different speckle images, the GoL speckle generated from our proposed method shows the smallest measurement error. This indicates that the proposed speckle patterns generating method could provide a new type of speckle pattern with better quality and accuracy.

Quality assessment of laser speckle image sequences for digital image correlation by Sequence-image Quality Evaluation Index

Digital Image Correlation (DIC) with laser speckle is effective for measuring strain in extreme conditions, but its limited resistance to disturbances and decorrelation issues limit its broader use. Addressing this, the Sequence-image Quality Evaluation Index (SQEI) has been introduced. SQEI evaluates laser speckle image sequences by considering individual image quality and their correlation. It improves upon previous standards by confirming speckle image quality for DIC accuracy and removing decorrelated images, enhancing DIC's precision and durability. Verified through metal thermal strain experiments, SQEI assesses the impact of factors like laser wavefront, temperature, and CCD angle. The results confirm SQEI's efficacy in evaluating laser speckle quality and guiding the optimization of optical devices, thus significantly boosting the accuracy and efficiency of DIC strain measurement with laser speckles.

Digital image correlation technique for failure and crack propagation of fibre-reinforced polymer composites – A review

Digital image correlation (DIC) is a powerful technique for determining material deformation and damage and currently is viewed as a potential method to study failure and crack propagation in advanced composite materials. Case studies in concrete, epoxy adhesives, and carbon/epoxy laminates demonstrate the effectiveness of the DIC technique in visualizing crack propagation. This review highlights the applications, challenges, and implementation of the DIC technique in the failure and crack propagation of fibre-reinforced polymer (FRP) composites. The important factors such as field of view, speckle pattern, and algorithm choice are discussed while emphasizing the need for careful selection and calibration. The review concludes by highlighting the significance of crack propagation studies for composite behaviour and the role of DIC in calibrating and validating models of composite failure analysis. Future research directions include investigating mixed-mode delamination, improving calibration procedures, assessing DIC accuracy for large deformations, and comparing different DIC algorithms, which are discussed.

Precision and accuracy of craniofacial growth and orthodontic treatment evaluation by digital image correlation: a prospective cohort study.

A precise and accurate method for structural superimposition is essential for analyzing dentofacial growth and orthodontic or surgical treatment in longitudinal studies. The errors associated with different superimposition methods have not yet been assessed in high-quality studies. This study aimed to assess the precision and accuracy of digital image correlation (DIC) for structural superimposition. Two cephalometric images from 30 consecutive patients were superimposed using three DIC methods, each measured twice by two examiners. Areas including the contours of the sella, the whole cranial base (CB), and Walker's point and lamina cribrosa (WPLC) were compared using a random coefficient model. Inter-rater and intra-rater errors were assessed for each method. WPLC provided the best precision for image rotation and cephalometric landmarks. Systematic bias was observed between the WPLC and CB methods for image rotation and most landmarks. The intra-rater error in image rotation during DIC was strongly correlated with the intra-rater error in the landmarks of the anterior nasal spine, articulare, and pogonion. Structural superimposition using DIC with WPLC is a precise method for analyzing dentofacial growth and orthodontic or surgical treatment. Moreover, the best method is the measurement of longitudinal dental and craniofacial changes on structurally superimposed cephalometric radiographs with WPLC and a reference grid including the true vertical and horizontal lines from Walker's point.

Point cloud optimization of multi-view images in digital image correlation system

Post-processing of the initial point cloud is one of the important ways to improve the measurement accuracy of digital image correlation (DIC). In this study, a multi-level point cloud optimization scheme is proposed for processing point clouds of multi-view images in DIC systems. Dense point clouds obtained after interpolation of primary point clouds from multi-view images contain noise. First, the local Random Sample Consensus (RANSAC) algorithm is proposed to retain local features while removing coarse matching points. Defects are filled in by the adaptive cavity repair technique based on information around the cavities and restores the original surface shape to the greatest extent. Finally, a multi-layer surface filtering is executed to smooth the mesh. Experiments verify the comprehensive performance of the multi-level optimization scheme, providing excellent results in point cloud fusion, cavity repair, and mesh smoothing, regardless of static 3D reconstruction or dynamic deformation measurement.

Adjusting Accuracy of Digital Image Correlation Through Variable Subsets and Application in Airship Envelope

Adjusting Accuracy of Digital Image Correlation Through Variable Subsets and Application in Airship Envelope

Investigation of the accuracy of Digital Image Correlation (DIC) in measuring full-field strain for timber materials

As one of the most successful techniques in experimental mechanics, digital image correlation (DIC) has been widely used to measure the motion and deformation of solid materials, especially in situations where non-contact measurement is required. This study describes and provides a comprehensive overview of the application of DIC using the open-source platform Ncorr on orthotropic materials. Orthotropic materials are a subset of anisotropic materials; their properties depend on the direction in which they are measured. Deformation displacement and in-plane strain in two directions are extracted from digital image correlation using a reference image recorded during the experiment. Tests are carried out on Laminated Veneer Lumber timber specimens according to the ASTM standard to determine the mechanical properties of materials under compression. DIC has proven to be a reliable, consistent, and cost-effective non-contact deformation measurement method that can assist in the extraction of mechanical properties of orthotropic materials. This study also showed that DIC analysis with a natural timber grain can be used to measure the displacement and strain fields of the material.

Mechanical Property Test of Grass Carp Skin Material Based on the Digital Image Correlation Method.

Fish is a common and widely distributed creature. Its skin has a unique physiological structure and plays an important role in many fields. Fish skin also has important potential value for bionics research. This study aims to provide a method and a reliable data for the study of bionics. A method of measuring the mechanical properties of fish skin samples using a binocular stereo digital image correlation (DIC) system combined with a synchronous tensile testing machine was proposed. The mechanical properties (e.g., elastic modulus E and strain) of grass fish skin samples (GFSA) were tested in hydrophilic and dry states. A dual-frequency laser interferometer was used to calibrate the tensile testing machine synchronously, and the feasibility and strain accuracy of DIC in GFSA measurement were verified by finite element method (FEM). The results show differences in the mechanical properties of GFSA between different individuals, different parts, and different states. Under the same stress, the head was easy to deform, and the strain was the largest, and E was the smallest. The tail result was the opposite of the head result.

Defects localization using the data fusion of laser Doppler and image correlation vibration measurements

This work proposes a defects localization method based on the combination of laser Doppler vibrometry (LDV) and Digital image correlation (DIC). DIC and LDV are the dominant non-contact vibration measurement methods with a matured theory and high stability. DIC gives a high spatial resolution with a measurement accuracy of several microns, whereas the Multipoint LDV has a limited spatial resolution with high-precision results for the sparse points up to nanometer level. However, the vibration-based defect localization (VBDL) necessitates certain measurement methods with both the high spatial resolution and measurement accuracy. Unfortunately, the accuracy of DIC is not sufficient to detect the data anomalies caused by the structural defects. Nevertheless, LDV cannot achieve a high-precision defect localization owing to the limited spatial resolution. In this study, a nonlinear weighted least-squares fitting has been proposed to improve the measurement accuracy and reliability. A Chebyshev polynomial has been employed as the basis function in the fitting process. The effective signal-to-noise ratio (SNR) and the correlation coefficient are employed as the weight basis of the LDV points and the DIC subsets, respectively. Based on the simulation analysis, the determination of the optimal polynomial order at multiple noise levels and the influence of the LDV points distribution are discussed. The experiment proves that the data fusion method can significantly improve spatial resolution and measurement accuracy. From the data fusion results, the reference-free defects localization in cantilever beams and plates based on residuals have been presented.

Application of Ultraviolet (UV) Radiation and Fluorescence for DIC Measurements - Quality Improvement

Digital image correlation (DIC) is a widely used method in materials science and experimental mechanics for full-field surface displacement or strain measurements. It is an optical method, which calculates displacement or strain fields from images taken during deformation of the test specimen and is able to achieve a sub-pixel accuracy in case of proper operation. However, the theoretical accuracy is strongly reduced by effects such as surface reflections or shadows resulting from a not ideal illumination or lighting system. This is especially the case for complex 3D structured specimen geometries such as for metal foams or other cellular materials.The present study investigates the usage of ultraviolet (UV) light illumination in combination with phosphorescent or fluorescent pigments used to apply the needed speckle pattern for high accuracy DIC. A method to optimise the lighting system in combination with the used background pigments is presented. Fluorescent pigments provide much better results than phosphorescent pigments. The application of UV lighting in combination with fluorescent background pigments strongly improves DIC accuracy not only for normal tensile specimens but also for complex 3D shaped metal foams by avoiding surface reflections and shadows.

A simple and effective way to evaluate the accuracy of digital image correlation combined with scanning electron microscopy (SEM-DIC)

Digital image correlation (DIC) is a powerful technique enabling mapping of local strain fields with the spatial resolution down to a few nanometers when combined with scanning electron microscopy. However, the accuracy of strain determination is frequently unknown due to a large number of experimental parameters influencing it. Here we present a simple and time-effective method for quantitative evaluation of uncertainties in strain values obtained by DIC. By imposing a fictive hydrostatic strain a high absolute accuracy of mean strain determination is demonstrated with deviations from the target value below 0.03%. At the same time, the precision decreases strongly with the reduction of the subset and step sizes reflecting a fundamental tradeoff between the spatial resolution and trueness of local strain values.

Effect of speckle size on surface crack detection via digital image correlation

Digital image correlation (DIC) is an experimental stress analysis technique used in nondestructive tests. The accuracy of DIC in crack detection depends on various factors such as the sizes of speckles and pixels. In the current study, a speckle pattern based on the spreading of nanoparticles with small speckles is compared with a conventional sprayed pattern to understand whether crack detection via DIC is improved by reducing the sizes of speckles and pixels. Owing to the small size of nanoparticles, an optical microscope is used for magnification. The spreading method for crack detection is first investigated experimentally. Results show that cracks can be detected easily when a 250 nm opening appears in the crack edges. Subsequently, the spreading method is compared with the conventional DIC, in which the spraying method is used for patterning, in terms of crack detection. Results show that by reducing the speckle size and closely analyzing the speckle pattern, the DIC technique is considerably better than the conventional technique in detecting small cracks. Moreover, the conventional method is more suitable for detecting large cracks.

Measurement and identification of the nonlinear dynamics of a jointed structure using full-field data, Part I: Measurement of nonlinear dynamics

Jointed structures are ubiquitous constituents of engineering systems; however, their dynamic properties (e.g., natural frequencies and damping ratios) are challenging to identify correctly due to the complex, nonlinear nature of interfaces. This research seeks to extend the efficacy of traditional experimental methods for linear system identification (such as impact testing, shaker ringdown testing, random excitation, and force or amplitude-control stepped sine testing) on nonlinear jointed systems, e.g., the half Brake–Reußbeam, by augmenting them with full-field data collected by high-speed videography. The full-field response is acquired using high-speed cameras combined with Digital Image Correlation (DIC), which enables studying the spatial–temporal dynamic characteristics of the system. As this is a video-based experiment, additional constraints are attached to the beam at the node points to remove the rigid body motion, which ensures that the beam is in the view of the camera during the entire test. The use of a video-based method introduces new sources of experimental error, such as noise from the high-speed camera’s fan and electrical noise, and so the measurement accuracy of DIC is validated using accelerometer data. After validating the DIC data, the measurements are recorded for several types of excitation, including hammer testing, shaker ringdown testing, fixed sine testing, and stepped sine testing. Using the DIC data to augment standard nonlinear system identification techniques, modal coupling and the mode shapes’ evolution are investigated. The suitability of videography methods for nonlinear system identification of nonlinear beams is explored for the first time in this paper, and recommendations for techniques to facilitate this process are made. This article focuses on developing an accurate data collection methodology as well as recommendations for nonlinear testing with DIC, which paves the way for video-based investigation of nonlinear system identification. In Part-II (Jin et al., 2021) of this work, the same data set is used for a rigorous assessment of nonlinear system identification with full-field DIC data.

Investigating the accuracy of digital image correlation in monitoring strain fields across historical tapestries

AbstractFinite element generated synthetic image deformation is used to assess factors affecting the reliability and accuracy of strain fields measured by the DIC technique, when using the inherent historical tapestry image to track deformations. Compared with direct correlation with the reference image, incremental correlation is found to introduce accumulated error and is less suitable for DIC analysis under low strains. Image quality, for example, variation in resolution, is demonstrated to strongly affect DIC performance. Finally, it is recommended that an iterative approach is required to determine the optimum subset and strain filter size for effective DIC analysis using inherent tapestry patterns, especially at low strain levels.

Non-uniform illumination correction based on multi-scale Retinex in digital image correlation.

Digital image correlation (DIC) is an effective optical measurement method. It aims to obtain the displacement field and strain field of the measured object by correlating two digital speckle images before and after deformation. In the actual acquisition of speckle images, due to the large volume of the measured object, the light source cannot cover all areas evenly or has some random change. These issues may easily lead to a non-uniform distribution of light intensity speckle images and reduce the quality of speckle images, which affects the accuracy of DIC measurement to a certain extent. To solve this problem, a non-uniform illumination correction algorithm based on multi-scale Retinex is introduced. First, to analyze the influence of non-uniform illumination on DIC measurement accuracy, the displacement comparison experiment of the numerical simulation speckle images with different non-uniform illumination is conducted. Then, a non-uniform illumination correction algorithm based on multi-scale Retinex is applied to reduce or eliminate the effects of non-uniform illumination by the simulation experiment. Finally, the quantitative measurement of rigid body rotation and uniaxial tensile experiment in plane is studied to verify the feasibility of the correction method for the speckle images. The experimental results show that the measurement accuracy of DIC is improved significantly with the aid of non-uniform illumination variation correction.