Conventional Digital Image Correlation Research Articles

Analysis of the Meso‐Mechanical Deformation Behavior of Al Foams and Ni/Al Hybrid Foams Using Time‐Lapse Micro‐Computed Tomography Measurements and 3D Optical Flow

Metal foams are an interesting class of bio‐inspired materials for lightweight construction and energy absorption. Commonly, aluminum (Al) foams are used. However, the mechanical properties have been improved by coating pure Al foams with a nanocrystalline nickel (Ni) coating resulting in Ni/Al hybrid foams. Herein, the meso‐mechanical deformation mechanisms in Al foams and the changes in the mechanisms in Ni/Al hybrid foams are studied using time‐lapse micro‐computed tomography measurements in comparison between numerical modeling using voxel finite element models and evaluation of displacement fields using 3D optical flow. This gives never‐seen insights into the highly localized 3D deformation mechanisms within the entire volume of the foams and not only on the surfaces as given by conventional digital image correlation methods. Displacements calculated by the 3D optical flow algorithm demonstrate its possibility to reveal a significant concentration of plastic deformation, particularly evident when deformation occurs within a distinct, slightly inclined band in the central region. Common numerical simulations using standard plasticity models do not accurately capture this localized deformation, underscoring the need to integrate damage and softening models into the simulation.

Application of Digital Image Correlation in Cross Weld Tensile Testing: Test Method Validation

This study addresses the limitations of cross weld tensile testing (CWTT) in quantifying local mechanical properties across microstructural and compositional gradients in dissimilar– and matching–filler metal welds. A digital image correlation (DIC) methodology was validated for application in CWTT by direct comparison of stress-strain curves generated using conventional and virtual DIC extensometers in tensile testing of homogeneous steel samples. DIC-instrumented CWTT of dissimilar weld metal Alloy 625 filler metal on F65 steel demonstrated capability in quantifying the local yield strength, strain-hardening kinetics, and strain at failure in the base metal, heat-affected zone (HAZ), fusion boundary (FB) region, and weld metal in dissimilar and matching filler metal welds. It was shown that the high strain-hardening capacity in Alloy 625 weld metal led to base metal failure in CWTT despite the lower Alloy 625 weld metal yield strength. It was also shown that DIC-instrumented CWTT can be used for determining weld metal undermatching and overmatching conditions in compositionally matching- and dissimilar-metal welds. Furthermore, by quantifying local strain distribution (both elastic and plastic) in the HAZ, FB region, and weld metal, DIC-instrumented CWTT provides an additional method for evaluating hydrogen-assisted cracking susceptibility in dissimilar-metal welds.

Unified digital image correlation under meshfree framework

AbstractThe implementation of digital image correlation (DIC) involves several different problems, such as image prefiltering, image intensity gradient calculation, image intensity interpolation at subpixel positions, shape function construction and strain calculation. This paper offers a unified insight into the nature of several key problems in DIC technique. We treat all the problems involved in the former mentioned key steps as fundamentally the same problem, that is, reconstructing an analytical description from a discrete and noisy sampling of a signal, such as discrete image intensity and displacement at some scattered nodes. From the reconstructed analytical description, the gradient and physical value at subpixel or integral pixel position can be analytically calculated without extra error. Here, we solve all these problems using the same mathematical tool, the meshfree method, leading to a unified DIC (U‐DIC) method. This method introduces errors solely during the steps involving the determination of the continuous description. However, it effectively avoids errors in the remaining steps. It holds the best balance between spatial resolution and measurement resolution for both displacement and strain measurements compared to 28 state‐of‐the‐art DIC algorithms based on the benchmark tests on DIC Challenge 2.0. It also holds all the unique advantages of the advanced meshfree DIC (MF‐DIC) compared to conventional local DIC and global DIC. The novel concept and excellent balance between spatial resolution and measurement resolution make U‐DIC an attractive replacement for conventional DIC methods. Additionally, the consistency of the implementation procedures in U‐DIC can simplify the parameter selection in DIC, which is of potential for the standardization of DIC technique.

Neutralizing the impact of heat haze on digital image correlation measurements via deep learning

Digital image correlation (DIC) techniques have shown excellent capabilities in the deformation measurements of materials and structures at high temperatures. However, as a crucial challenge for the high-temperature DIC measurements, heat haze, caused by uneven distributions of temperatures and refractive indices, can lead to considerable distortions to the captured images and severely decrease the measurement accuracy. Inspired by a recently established atmospheric turbulence neutralization neural network called TSR-WGAN, we propose a deep learning-based approach to neutralize the effect of heat haze on high-temperature DIC measurements. Specifically, the original distorted speckle images obtained in the experiment are fed into the TSR-WGAN network twice to obtain distortion-corrected speckle images. By processing these corrected speckle images with a conventional DIC algorithm, displacement and strain fields with mitigated heat haze effects can be determined. Both simulation and real experiments have been conducted to assess the proposed method. Results clearly show the effectiveness and robustness of the proposed method in correcting heat haze effects. One of the experiments particularly shows that the displacement fluctuations caused by the heat haze can be reduced by approximately an order of magnitude in the u direction and by a factor of five in the v direction. The proposed technique provides a much-needed tool for neutralizing the impact of heat haze on the DIC measurements under a high-temperature environment.

Improved SURF method in digital image correlation for estimation of large rotation angle

Digital image correlation (DIC) is widely used in optical measurement techniques with the advantages of high precision, robustness and expansibility. The conventional DIC, however, is highly dependent on the accuracy of initial parameters, and there are reports [1,2] that it may fail when the rotation angle of the target specimen exceeds 7°. The combination of Speeded-Up Robust Features (SURF) with Random Sample Consensus (RANSAC) algorithm has been applied to solve this problem with limited success due to the effects of residual mismatches. An enhanced algorithm based on SURF is proposed in this study to address this problem. The transformation model between two images is obtained by RANSAC similar to existing methods. Then an angle compensation strategy is proposed to estimate the rotation angle of the deformed image to form the compensated image. Finally, an iterative process is proposed to refine the initial parameters from the reference and deformed images with a new convergence threshold. In addition, an evaluation criterion developed from a multiple ring template is proposed to compute the similarity of feature point pairs to improve the speed of convergence and sampling accuracy. Results from numerical simulation and experimental analysis show that the accuracy and robustness of the proposed method are significantly improved. Further application of the proposed method to monitor the rotating blades of a scaled model wind turbine illustrates further the capability of the proposed method.

Snapshot compressive imaging based digital image correlation: temporally super-resolved full-resolution deformation measurement.

The limited throughput of a digital image correlation (DIC) system hampers measuring deformations at both high spatial resolution and high temporal resolution. To address this dilemma, in this paper we propose to integrate snapshot compressive imaging (SCI)-a recently proposed computational imaging approach-into DIC for high-speed, high-resolution deformation measurement. Specifically, an SCI-DIC system is established to encode a sequence of fast changing speckle patterns into a snapshot and a high-accuracy speckle decompress SCI (Sp-DeSCI) algorithm is proposed for computational reconstruction of the speckle sequence. To adapt SCI reconstruction to the unique characteristics of speckle patterns, we propose three techniques under SCI reconstruction framework to secure high-precision reconstruction, including the normalized sum squared difference criterion, speckle-adaptive patch search strategy, and adaptive group aggregation. For efficacy validation of the proposed Sp-DeSCI, we conducted extensive simulated experiments and a four-point bending SCI-DIC experiment on real data. Both simulation and real experiments verify that the Sp-DeSCI successfully removes the deviations of reconstructed speckles in DeSCI and provides the highest displacement accuracy among existing algorithms. The SCI-DIC system together with the Sp-DeSCI algorithm can offer temporally super-resolved deformation measurement at full spatial resolution, and can potentially replace conventional high-speed DIC in real measurements.

Digital image correlation based on convolutional neural networks

As an indispensable non-destructive testing technique, digital image correlation (DIC) has been increasingly applied to various engineering areas concerning deformation characterization. Inspired by artificial intelligence-related technologies, we here develop a new convolutional neural network-based theoretical framework for DIC analyses, hereafter called DIC-Net. A pyramidal structure is designed to ensure robustness and reliability of measurement results. Simultaneously, the second-order shape function is adopted to create training dataset, making the DIC-Net more suitable for solving complex deformation fields. Different from conventional DIC algorithms, the developed DIC-Net does not require specific correlation criterion, nor is it necessary to perform numerical iterative computations, which greatly enhances the efficiency of correlation calculations. The proposed DIC-Net not only provides an alternative approach to achieve accurate, precise and reliable deformation measurements, but also paves the way for developing high-efficiency DIC with real-time processing capabilities.

A novel rotated sigmoid weight function for higher performance in heterogeneous deformation measurement with digital image correlation

Conventional digital image correlation (C-DIC) combined with a rotated Gaussian weight (RGW) function for subset has demonstrated attractive ability in resolving heterogeneous deformation parameters. To further improve the performance, the selection of an optimum weight function becomes the key issue. In this paper, a novel rotated sigmoid weight (RSW) function is proposed. RSW function aims to get a more uniform weight distribution near the subset center, and to realize the continuous change of the equivalent subset size as well. The performance of the RSW function is compared with the Gaussian weight (GW) function, RGW function, the rotated inverse distance weight (RIDW) function and the inverse distance square weight (RIDSW) function through Star 5 image set from the DIC challenge 2.0 and the simulated image set. A total of six methods with different weight functions and rotated weights are systematically compared. The experiment results clearly show that DIC combined with RSW function (i.e. RSW-DIC) has the best spatial resolution without sacrificing much measurement resolution. The spatial resolution of RSW-DIC is only about half of the other methods for both first- and second-order shape functions when a big initial subset size is adopted.

Electroluminescent strain sensing on carbon fiber reinforced polymer

The present paper demonstrates an inexpensive and less labor-intensive machine vision-based strain and damage visualization technique compared to traditional carbon fiber reinforced polymer material inspection methods. This technique is used to characterize the fracture and failure properties upon progressive axial loading in textile carbon fiber reinforced polymer (CFRP) lamina with non-intrusive smart electroluminescent (EL) integration. The smart EL structure utilizes CFRP's unique conductive and piezoresistive properties to visualize deformation and cracks through brightness change. Two fiber orientations (±45° and 0°/90°) of twill-weave CFRP lamina are fabricated according to a modified ASTM D3039 for linear and fatigue loading in uniaxial mechanical tests to analyze both fiber and matrix-induced EL responses. The EL-strain visualization method is validated with standardized digital image correlation (DIC) utilizing the natural speckling pattern of the EL CFRP lamina. The axial EL-strain results for both static and cyclic loading highly agree with the strain extracted planar conventional DIC strain field on standard and damaged CFRP samples in terms of spatial resolution and sensitivity. This novel strain and damage visualization method aims to be a portable, low-cost, and real-time alternative to non-destructive testing methods commonly used in the composite industry. Instead of periodic checkups, EL architecture allows for real-time strain and damage visualization of composite structure. • Fabrication and tensile testing of strain sensing EL illuminating woven CFRP in [±45°] and [0°/90°] fiber orientations. • Visual damage and strain detection are achieved with EL CFRP structure. • Planar DIC strain fields produced on EL illuminating and conventional airbrushed patterns show strong correspondence. • Variations in piezoresistive and luminance response exhibit correlation with strain.

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.

Microcrack characterization of loaded Engineered Cementitious Composites via optical scans and photogrammetric analyses

Concrete cracks accelerate the ingress of harmful species and must be gauged accurately for durability evaluation and prediction. As a novel class of ultra-ductile concrete, Engineered Cementitious Composites (ECC) develops multiple sub-hairline cracks that are difficult to visualize using conventional techniques. In this study, a semi in-situ laboratory approach is proposed based on optical microscopy and photogrammetric analysis to enhance the accuracy of crack width measurement in ECC. Microscopic images scanned from the material surface were reconstructed and analyzed to extract the statistics of crack width, location, number, and spacing. Results suggested that general portable microscopes can effectively identify cracks smaller than 2 µm in loaded condition and provide magnified high-resolution crack images that are hardly achieved by regular digital cameras. Crack openings can be isolated via 2D FFT filtering and binarized to attain the datasets of crack spacing and crack width distribution. In contrast to microscopy, conventional digital image correlation (DIC) as an indirect method was found to overestimate sub-pixel crack widths particularly when the crack width and spacing are substantially smaller than the image resolution. In these scenarios, it is recommended to combine optical microscopy with DIC to ensure simultaneously accurate and holistic crack width characterization. The proposed technique can be used for general materials with multiple fine cracks.

In situ scanning–digital image correlation for high-temperature deformation measurement of nickel-based single crystal superalloy

In situ microscopic observation and measurement of deformations for advanced hot-section materials at high-temperature is helpful in understanding their failure mechanisms. Scanning electron microscopy (SEM) and a digital image correlation (DIC) method are combined to capture the failure process. This article reports an in situ high-temperature testing system which can heat the specimen up to 1000 °C and provide clear images simultaneously. The Al2O3 nanoscale particles are developed as high-temperature deformation carriers in SEM–DIC, which are suitable for high-temperature samples with significant advantages of stability, high image contrast and without shedding or melting up to 1000 °C. High-temperature tensile and creep properties of a nickel-based single crystal superalloy (NBSCS) at 750 °C were investigated using this system. In addition, a scanning–DIC (S–DIC) method, which avoids errors introduced by conventional DIC methods, was used to calculate full-field dynamic displacement and strain of high-temperature NBSCS samples. Analysis of the strain fields show that the strain concentrations are generally at the positions of crack initiation or propagation, and the creep cracks interact with each other through the strain field. Finally, the crack opening displacement is obtained using the virtual extensometer.

Evaluation of crack opening phenomenon using subset-optimized digital image correlation

This paper presents crack opening phenomenon evaluation using digital image correlation (DIC) with a statistically optimized subset size. In conventional DIC analysis, the subset sizes varying from several pixels to more than hundred pixels have been often selected by experts' subjective judgement based on conventional subset size determination algorithms. Since these conventional subset size determination algorithms, however, calculate speckle pattern features at a certain location of a single target image, it is difficult to consider not only all speckle pattern features within region of interest (ROI) but also the random measurement noises during the digital image acquisition process. To overcome the technical limitation, a statistical optimization algorithm of the subset size, which calculates the optimal subset size by the 3-loop iteration of normalized cross correlation within the entire ROI, is newly proposed. In addition, the optimal subset-based DIC analysis is applied to crack opening phenomenon evaluation in a mock-up concrete specimen under step loading conditions. The validation test results show 3.6 μm maximum error compared with the ground truth which is obtained by direct measurement, while a conventional subset size determination algorithm-based DIC analysis produces the maximum error of 62.7 μm.

Boundary Deformation Measurement by Mesh-Based Digital Image Correlation Method

Digital image correlation (DIC) is a popular photomechanics method for deformation measurement. The conventional subset-based DIC method obtains the displacement vectors at the subset centers, but cannot calculate the deformation on the specimen edges, which may contain very useful information because specimens usually have greater deformation on edges, especially on curved edges due to stress concentration. In this study, the capability of a mesh-based DIC method using 8-node quadrilateral elements (Q8-mesh-DIC) in boundary deformation measurement was investigated and highlighted for specimens with non-uniform deformation. The results were compared with those obtained by some conventional subset-based DIC methods, and the accuracy of the boundary deformation measurement was verified through simulated and real experiments. The Q8-mesh-DIC appears to be more suitable for the boundary deformation measurement of non-uniform deformation fields.

In vivo panoramic human skin shape and deformation measurement using mirror-assisted multi-view digital image correlation

Panoramic shape and deformation measurements of human skin in vivo may provide important information for biomechanical analysis, exercise guidance and medical diagnosis. This work proposes the application of an advanced mirror-assisted multi-view digital image correlation (DIC) method for dynamic measurements of 360-deg shape and deformation of human body parts in vivo. The main advantage of this method consists in its capabilities to perform full-panoramic non-contact measurements with a single pair of synchronized cameras and two planar mirrors thus representing a lean yet effective alternative to conventional multi-camera DIC systems in ‘surrounding’ configuration. We demonstrate the capabilities of this method by measuring the full-panoramic shape of a plastic human head, the deformation of a woman face and the principal strain distribution over the full-360-deg surface of a forearm during fist clenching. The applications of this method can be the most disparate but, given the possibility to determine the full-field strains and derived information (e.g. skin tension lines), we envisage a great potential for the study of skin biomechanics in vivo.

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.

Dynamic Visible Monitoring of Heterogeneous Local Strain Response through an Organic Mechanoresponsive AIE Luminogen.

Local strain concentration is critically important for damage formation of structural components. Therefore, it is of particular interest in developing the structural health monitoring (SHM) method for large-scale, full-field, and on-site monitoring of local strain response in complicated structural components in service. The present work investigated a SHM method based on a pure organic mechanoresponsive luminogen (MRL), 1,1,2,2-tetrakis(4-nitrophenyl)ethane, for heterogeneous local strain concentration. Invisible heterogeneous local strain response in complicated weld joints is transformed into visible fluorescence under monotonic tension and cyclic stress loading. The local strain (<15%) calculated by fluorescence intensity has a good agreement with the results obtained by the conventional digital image correlation method, indicating good measurement accuracy of the calibrated organic MRL method. The heterogeneity of local strain in complicated weld joints increases along with elongation and number of stress cycles. Moreover, the higher mean stress and stress amplitude can induce significantly higher accumulated local strain in the relatively soft fusion zone region. Compared with conventional strain measurement methods, the present organic MRL method opens up new possibilities for large-scale, full-field, and on-site monitoring of local strain concentration and damage in complicated structural components.

Measurement of large, discontinuous displacement from digital images

AbstractOne main limitation of conventional digital image correlation (DIC) methods is their incapacity to treat with large, discontinuous displacements. This paper seeks to resolve this issue using a variational method. Specifically, the objective function is written in a form of L1‐norm instead of L2‐norm for discontinuity preservation. This convex, non‐differentiable objective function is resolved by a proximal gradient method. Then, the entire correlation process is embedded into a multi‐level image pyramid, enabling large displacements to be measured accurately. The proposed method is first validated on images with prescribed small displacements; its performance to treat with discontinuous, large displacements is then examined. The results show that the proposed method exhibits an acceptable performance when measuring some extreme displacements up to 16.5 pixels in a 500 × 500 pixels resolution image. Concerning subpixel accuracy, the errors can be lessened to a very low level with optimised parameters even for a dense correlation at each pixel. Good performance is also demonstrated in forms of noise proof and illumination fluctuation tolerance. Finally, an application is conducted on an experiment concerned with cracking in desiccated soils, in which the proposed method succeeds in tracking the nucleation and propagation processes of multiple cracks.

Methods for measuring large shear strains in in-plane torsion tests

The in-plane torsion test achieves true strains far beyond 1.0 for sheet metals, especially using specimens with circular grooves. The accurate measurement of these high strains is a challenge for the conventional digital image correlation (DIC). Thus, the determination of flow curves is limited and fracture strains for very ductile materials cannot be measured. A new grooved specimen is introduced to avoid strain localization. Shear stress and shear strain along a defined area in the groove are constant so that strains can be measured independently of the DIC system setting without error due to strain localization. Furthermore, three methods for the measurement of very high shear strains in the in-plane torsion test are presented: Firstly, the limit of the optical strain measurement is extended by multiple renewal of the digital image correlation (DIC) pattern on the samples. Secondly, the shear strain for the planar specimen is calculated exactly from the rotation angle curve. Lastly, a new incremental method is presented. This method enables to determine shear strains for plane and grooved specimen exactly by only measuring the torque and the angle of rotation. All methods were applied for three steel sheet materials namely DP1000, CP1000 and DC04. The equivalent strain in a grooved in-plane torsion test of sheet steel DC04 was determined as 3.3 with the new incremental method. Such high strains far exceed conventional methods for determining the flow curve.

Polar transformation of 2D X-ray diffraction patterns and the experimental validation of the hDIC technique

Deformation analysis in engineering materials and components is a subject of ongoing enquiry due to its importance for obtaining reliable prediction of strength and durability of structures and assemblies. Whilst optical methods deliver information about surface displacements, X-ray scattering methods have the capability to provide efficient assessment of crystal lattice distortion in the bulk of the component. The height digital image correlation (hDIC) technique is an alternative to conventional digital image correlation that uses the out-of-plane surface height variations for the identification of triaxial deformations. In this study, the hDIC technique was used for the determination of displacements in an aluminium specimen after 3-point bending process that creates a complex deformation state that includes both axial displacements and rotations. The surface of the specimen was prepared for the analysis by electric discharge machining (EDM) technique that has minimal effect on material properties and produces random height profile well-suited for the aim of this study. Surface height variations were measured using deep focus microscopy and used instead of pixel intensity for correlation in the DIC process. The distribution of total of elastic and plastic strains were also calculated by the evolutionary eigenstrain model using 2D X-ray diffraction patterns processed according to the polar transformation method. The agreement between hDIC and polar X-Ray diffraction analyses allowed reliable cross-validation between these two techniques.