Accuracy Of Digital Image Correlation Research Articles

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.

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.

Variable subset DIC algorithm for measuring discontinuous displacement based on pixel-level ZNCC value distribution map

Digital image correlation (DIC) is one of the most used techniques for measuring deformation. It is widely used in mechanical performance testing, structural health monitoring and many other fields. The standard subset based DIC technology assumes that the deformation is continuous. However, discontinuous deformation such as cracks and dislocations are quite common in practical applications. The measurement accuracy of DIC in these areas will be significantly reduced, or even measurement failure. This is a limitation for the application of DIC. To overcome this problem, this paper proposes a variable subset DIC algorithm. Taking the zero-mean normalized cross-correlation (ZNCC) function as the correlation criterion, the concept of pixel-level ZNCC value distribution map is proposed. The proposed algorithm can automatically select the most suitable subset for matching under the guidance of the pixel-level ZNCC value distribution map. This method has the advantages of good flexibility, strong applicability, and high precision.

Estimating gray intensities for saturated speckle to improve the measurement accuracy of digital image correlation

Accuracy of digital image correlation (DIC) is deeply affected by illumination variation, especially the local pixel saturation exists. A simple and efficient gray intensity adjustment strategy based on feature matching and standard DIC method is presented for estimating the intensities of saturated pixels. Principle of the strategy based on surrounding pixels around the saturated pixel and the principle of the new proposed strategy are first detailed. Simulations and experiments are performed to verify the efficiency of the proposed strategy. The results indicate that the DIC measurements based on the proposed strategy are able to provide more reliable and accurate results as compared to the existing strategy, even though the large local speckles are saturated.

High-resolution optical microscopy for characterising microstructural deformation in microtensile testing.

Imaging surface deformation of a coupon specimen in microtensile testing with an optical microscope presents challenges due to the narrow depth of field (DoF) of optical microscopes. Materials being heterogeneous at microscopic length scale, the sample surface deforms into a complex 3D surface texture, evolving continuously as the loading increases. Because of the narrow DoF, the region that is in focus within the field of view (FoV) decreases substantially in size with the increasing out-of-plane heterogeneous deformation. To address this challenge, a method based on image blending and stabilisation of the captured image frames is proposed. Image blending combines the partial regions that are in focus from a set of successive image frames captured at different working distances from the object surface plane to construct a single image that has a large part of the FoV in focus. The blended images are then obtained at different levels of macroscopic strains, that is the global homogeneous strain, in order to characterise the evolution of the heterogeneous deformation. The image stabilisation removes any misalignments of the blended images by spatially realigning them choosing a common feature as a reference point. The validation of the proposed method with conventionally and additively manufactured stainless steel 316L (SS 316L) specimens demonstrates excellent improvement in image quality. Almost 100% of the FoV is maintained in focus regardless of the amount of out-of-plane heterogeneous deformation caused during tensile testing, which is quite remarkable for optical microscopy imaging. Consequently, the blended and stabilised images enhanced the accuracy of digital image correlation (DIC). Time-lapse videos of the deformation generated using these images captured the evolution of the slip bands and their transmission through twinning boundaries in the stainless steel microstructure. Overall, this study demonstrates the feasibility of using image-processing techniques to advance optical microscopy to image complex 3D surfaces evolving with time.

Influence of the implementation order of distortion correction and subset matching on digital image correlation

The shape function and lens distortion affect the accuracy of digital image correlation (DIC). Many studies have been conducted on the shape function and lens distortion correction, and an appropriate shape function with lens distortion correction can reduce measurement errors. However, the influence of the implementation order of correcting lens distortion with known distortion parameters and matching subsets with different shape functions has not been discussed. The two implementation orders are: correcting matched grid points after matching distorted subsets and correcting distorted images before matching the subsets. The former will cause undermatching, and the latter will produce additional interpolation errors. Simulations and an experiment with known lens distortion parameters were performed to evaluate the accuracy of the two implementation orders. The forward additive Gauss–Newton algorithm with first-order and second-order shape functions was applied to the measurements. The results show that the order of correcting distorted images before matching subsets has higher accuracy as compared with another order, and a second-order shape function should always be used unless the underlying deformation is known to be lower order.

Adaptive Subset-Based Digital Image Correlation for Fatigue Crack Evaluation

This paper proposes a fatigue crack evaluation technique based on digital image correlation (DIC) with statistically optimized adaptive subsets. In conventional DIC analysis, a uniform subset size is typically utilized throughout the entire region of interest (ROI), which is determined by experts’ subjective judgement. The basic assumption of the conventional DIC analysis is that speckle patterns are uniformly distributed within the ROI of a target image. However, the speckle patterns on the ROI are often spatially biased, augmenting spatially different DIC errors. Thus, a subset size optimization with spatially different sizes, called adaptive subset sizes, is needed to improve the DIC accuracy. In this paper, the adaptive subset size optimization algorithm is newly proposed and experimentally validated using an aluminum plate with sprayed speckle patterns which are not spatially uniform. The validation test results show that the proposed algorithm accurately estimates the horizontal displacements of 200 μ m , 500 μ m and 1 mm without any DIC error within the ROI. On the other hand, the conventional subset size determination algorithm, which employs a uniform subset size, produces the maximum error of 33% in the designed specimen. In addition, a real fatigue crack-opening phenomenon, which is a local deformation within the ROI, is evaluated using the proposed algorithm. The fatigue crack-opening phenomenon as well as the corresponding displacement distribution nearby the fatigue crack tip are effectively visualized under the uniaxial tensile conditions of 0.2, 1.0, 1.4 and 1.7 mm , while the conventional algorithm shows local DIC errors, especially at crack opening areas.