Digital Image Correlation Algorithm Research Articles

A Technique for In-Situ Displacement and Strain Measurement with Laboratory-Scale X-Ray Computed Tomography

Abstract Purpose: Establish a technique for simultaneous interrupted volumetric imaging of internal structure and time-resolved full-field surface strain measurements during in-situ X-ray micro-computed tomography (XCT) experiments. This enables in-situ testing of stiff materials with large forces relative to the compliance of the in-situ load frame, which might exhibit localization (e.g., necking, compaction banding) and other inhomogeneous behaviors.Methods: The system utilizes a combination of in-situ XCT, 2D X-ray imaging, and particle tracking to conduct volumetric imaging of the internal structure of a specimen with interrupted loading and surface strain mapping during loading. Critically, prior to the laboratory-scale XCT experiments, specimens are speckled with a high-X-ray-contrast powder that is bonded the surface. During in-situ loading, the XCT system is programmed to capture sequential 2D X-ray images orthogonal to the speckled specimen surface. A single particle tracking (SPT) or digital image correlation (DIC) algorithm is used to measure full-field surface strain evolution throughout the time-sequence of images. At specified crosshead displacements, the motion and 2D image sequence is paused for volumetric XCT image collection. Results: We show example results on a micro-tensile demonstration specimen additive manufactured from Inconel 718 nickel-chrome alloy. Results include XCT volume reconstructions, crosshead-based engineering stress, and full-field strain maps. Conclusion: We demonstrate an in-situ technique to obtain surface strain evolution during laboratory-scale XCT testing and interrupted volumetric imaging. This allows closer investigation of, for example, the effect of micro-pores on the strain localization behavior of additive manufactured metal alloys. In addition to describing the method using a representative test piece, the dataset and code are published as open-source resources for the community. Graphical abstract

Experimental Examination of Additively Manufactured Patterns on Structural Nuclear Materials for Digital Image Correlation Strain Measurements

Abstract Background There are a limited number of commercially available sensors for monitoring the deformation of materials in-situ during harsh environment applications, such as those found in the nuclear and aerospace industries. Such sensing devices, including weldable strain gauges, extensometers, and linear variable differential transformers, can be destructive to material surfaces being investigated and typically require relatively large surface areas to attach (> 10 mm in length). Digital image correlation (DIC) is a viable, non-contact alternative to in-situ strain deformation. However, it often requires implementing artificial patterns using splattering techniques, which are difficult to reproduce. Objective Additive manufacturing capabilities offer consistent patterns using programmable fabrication methods. Methods In this work, a variety of small-scale periodic patterns with different geometries were printed directly on structural nuclear materials (i.e., stainless steel and aluminum tensile specimens) using an aerosol jet printer (AJP). Unlike other additive manufacturing techniques, AJP offers the advantage of materials selection. DIC was used to track and correlate strain to alternative measurement methods during cyclic loading, and tensile tests (up to 1100 µɛ) at room temperature. Results The results confirmed AJP has better control of pattern parameters for small fields of view and facilitate the ability of DIC algorithms to adequately process patterns with periodicity. More specifically, the printed 100 μm spaced dot and 150 μm spaced line patterns provided accurate measurements with a maximum error of less than 2% and 4% on aluminum samples when compared to an extensometer and commercially available strain gauges. Conclusion Our results highlight a new pattern fabrication technique that is form factor friendly for digital image correlation in nuclear applications.

On the Compositional Step of the IC-GN Digital Image Correlation Algorithm

Digital Image Correlation (DIC) is a well-known experimental optical technique for measuring the displacement field based on the assumption that pixel intensity does not change with motion.DIC can be implemented using various alternative approaches. The most used in the Experimental Mechanics field are the Forward-Additive Gauss-Newton (FA-GN) and the Inverse-Compositional Gauss-Newton (IC-GN) formulations. The former corresponds to the original formulation proposed by Lucas and Kanade, while the latter was proposed by Baker and Matthews twenty years later. Although both formulations give the same results at the first order, their speed, convergency characteristic and noise robustness differ considerably. Nowadays, the IC-GN method is usually preferred because of its lower computational load and the significantly better noise sensitivity. However, the Inverse Compositional approach, as its name states, requires the inversion and composition of the displacement field, thus enforcing the use of invertible displacement fields. This can be a significant limitation because it may introduce an under-matching error in the solution.This work shows that a simple modification of the viewpoint makes the compositional step simpler, thus giving a DIC formulation as fast as that of the IC-GN, with the same noise-bias characteristic and without requiring an invertible displacement field.

Augmented-Resolution Digital image correlation algorithm for vibration measurements

Digital Image Correlation (DIC) is a widespread technique, and many different implementations were developed in the literature to optimize the algorithm performance. In this paper, a new DIC algorithm is optimized for vibration measurements, where the displacement amplitude drastically decreases with the increase in frequency. Even if high-resolution cameras are used, it is mandatory to use a DIC algorithm with reliable sub-pixel performance. DIC algorithms are generally optimized for large complex displacement fields, and they solve the sub-pixel problem by fitting correlation data through a second-order polynomial function. An innovative solution is proposed to push the sub-pixel accuracy and increase the signal-to-noise ratio of the measurement, by exploiting image resizing to achieve virtual higher resolutions and by adopting a quartic polynomial function to interpolate the displacement map with an increased number of interpolation points. The proposed algorithm is validated through synthetic and experimental data and compared to literature DIC algorithms.

Using digital image correlation (DIC) to measure railway ballast movement in full-scale laboratory testing of sleeper lateral resistance

A fast and accurate method is described for determining the surface movement of railway ballast during a full-scale lateral resistance test. The proposed method utilises commodity camera equipment and open-source Digital Image Correlation (DIC) algorithms, to track individual ballast particles. It does not require time intensive ballast preparation. Tests have been performed under ambient and floodlit conditions, using colour and greyscale processing routes. The results are compared against direct measurements from lateral resistance tests to assess the accuracy of the proposed method, with a range of absolute maximum error between 0.9% and 3.4% under different laboratory conditions. The study shows that this technique is a viable way to track and measure ballast and sleeper movement over wide areas in near real time, which will lead to an increased understanding of the way ballast interactions influence track behaviour.

Effect of density grading on the mechanical behaviour of advanced functionally graded lattice structures

Lattice structures have found significant applications in the biomedical field due to their interesting combination of mechanical and biological properties. Among these, functionally graded structures sparked interest because of their potential of varying their mechanical properties throughout the volume, allowing the design of biomedical devices able to match the characteristics of a graded structure like human bone. The aim of this works is the study of the effect of the density grading on the mechanical response and the failure mechanisms of a novel functionally graded lattice structure, namely Triply Arranged Octagonal Rings (TAOR). The mechanical behaviour was compared with the same lattice structures having constant density ratio. Electron Beam Melting technology was used to manufacture titanium alloy specimens with global relative densities from 10% to 30%. Functionally graded structures were obtained by increasing the relative density along the specimen, by individually designing the lattice's layers. Scanning electron and a digital microscopy were used to evaluate the dimensional mismatch between actual and designed structures. Compressive tests were carried out to obtain the mechanical properties and to evaluate the collapse modes of the structures in relation to their average relative density and lattice grading. Open-source Digital Image Correlation algorithm was applied to evaluate the deformation behaviour of the structures and to calculate their elastic moduli. The results showed that uniform density structures provide higher mechanical properties than functionally graded ones. The Digital Image Correlation results showed the possibility of effectively designing the different layers of functionally graded structures selecting desired local mechanical properties to mimic the different characteristics of cortical and cancellous bone.

Conditional diffusion model-based generation of speckle patterns for digital image correlation

Generating speckle images is crucial for calibrating errors in digital image correlation (DIC) algorithms, alleviating the scarcity of training data for deep learning-based DIC algorithms, and even for the broader application of digital speckle methods. Traditional methods for speckle image synthesis struggle to accurately replicate the brightness variations in the foreground and background of realistic speckle images, and these methods come with high computational costs. Additionally, there needs to be more scientific and systematic evaluation methods for the quality of generated DIC speckle images. Our study presents a high-fidelity method for generating DIC speckle images with cracks based on a conditional diffusion model. We established evaluation metrics for generated DIC speckle images based on multiscale spatial and spectrum domains. We verified them on an open-source dataset of DIC speckle images depicting cracks in stone masonry walls. The conditional diffusion model excels at forward tasks (DIC crack image segmentation) and inverse tasks (DIC speckle image generation), with particular strength in the latter. The proposed spatial and multiscale spectrum domain metrics allow for the comprehensive and accurate evaluation of the alignment between the synthetic and natural speckle images. The conditional diffusion model for DIC speckle image generation and evaluation proposed in this paper has the potential to enhance further the accuracy and robustness of DIC technology in experimental mechanics and engineering applications.

Investigations on tensile mechanical properties of rigid insulation tile materials at elevated temperatures based on digital image correlation algorithm

This work investigates the tensile mechanical properties of rigid insulation tile (RIT) materials at room temperature (26 °C) and elevated temperatures (700–1000 °C) through experimental and digital image correlation (DIC) methods. Experimental results indicate that the tensile strength of RIT materials changes nonlinearly with increasing temperature and that the primary fracture mode under tension load is fiber root fracture. In terms of the DIC algorithm, this work builds an elevated-temperature DIC test system. A zero-mean Gaussian filtering algorithm and an image gradient difference square sum algorithm (SSDGI) are proposed to improve the precision of the DIC algorithm. The derived tensile stress-strain curve of RIT materials reveals that the elastic modulus changes nonlinearly with increasing temperature. The reliability and precision of the DIC algorithm are confirmed through the tensile test of silicon carbide particle-reinforced aluminum matrix composites. Hence, this work provides guidance for evaluating mechanical properties of RIT materials under elevated temperature environments.

Parameter identification of a phase-field fracture model using integrated digital image correlation

Phase-field fracture (PFF) modeling is a popular approach to model and simulate fracture processes in solids. Accurate material parameters and boundary conditions are of utmost importance to ensure a good prediction quality of numerical simulations. In this work, an Integrated Digital Image Correlation (IDIC) algorithm is proposed to calibrate boundary conditions, Poisson’s ratio, fracture energy and internal length, all at once, by using the phase-field model itself and images of a deforming sample. The presented approach is applied to virtual experiments mimicking a single edge notched shear test and implemented in the open-source deal.II-based software pfm-cracks and the digital image correlation library Correli 3.2. The reliability of the results is investigated for different levels of acquisition noise, thereby demonstrating high robustness and accuracy for a wide range of noise levels. The conditioning of the problem is analyzed via sensitivity fields for all parameters and the eigendecomposition of the Hessian matrix used in the IDIC algorithm.

Systematic Quantification and Assessment of Digital Image Correlation Performance for Landslide Monitoring

Accurate and reliable analyses of high-alpine landslide displacement magnitudes and rates are key requirements for current and future alpine early warnings. It has been proved that high spatiotemporal-resolution remote sensing data combined with digital image correlation (DIC) algorithms can accurately monitor ground displacements. DIC algorithms still rely on significant amounts of expert input; there is neither a general mathematical description of type and spatiotemporal resolution of input data nor DIC parameters required for successful landslide detection, accurate characterisation of displacement magnitude and rate, and overall error estimation. This work provides generic formulas estimating appropriate DIC input parameters, drastically reducing the time required for manual input parameter optimisation. We employed the open-source code DIC-FFT using optical remote sensing data acquired between 2014 and 2020 for two landslides in Switzerland to qualitatively and quantitatively show which spatial resolution is required to recognise slope displacements, from satellite images to aerial orthophotos, and how the spatial resolution affects the accuracy of the calculated displacement magnitude and rate. We verified our results by manually tracing geomorphic markers in orthophotos. Here, we show a first generic approach for designing and optimising future remote sensing-based landslide monitoring campaigns to support time-critical applications like early warning systems.

The Contribution of Digital Image Correlation for the Knowledge, Control and Emergency Monitoring of Earth Flows

Earth flows are complex geological processes that, when interacting with linear infrastructures, have the potential to cause significant damage. Consequently, conducting comprehensive investigations and continuous monitoring are becoming paramount in designing effective mitigation measures and ensuring sustainable risk management practices. The use of digital image correlation (DIC) algorithms for the displacement monitoring of earth flows is a relatively new and growing field with a limited number of dedicated works in the literature. Within this framework, the present paper contributes by evaluating DIC techniques at several earth flow sites. These assessments were founded upon data obtained from both low-cost and multi-platform sensors, used to assess the displacement field, pinpointing the most active sectors, and gauging their rates of movement during different kinematic phases. In this regard, the highest localized movement velocities reached in the Pietrafitta (0.01 m/day) and Grillo (0.63 m/day) earth flows experience different ongoing kinematic processes. The versatility of these techniques is notable, manifesting in the ease of installation, cost-effectiveness, and adaptability to various platforms. The proven reliability in terms of maximum accuracy (1 pixel) and sensitivity (0.05 m) lays the foundation for the extensive use of the presented techniques. The amalgamation of these attributes positions DIC techniques as competitive, adaptable, and readily deployable tools in earth flow studies.

The movement pattern of particles on the surface of liquid marble during rupture based on the DIC algorithm

The stability of liquid marbles is critical to their application in sensors, microfluidic control, microreactors, and other fields. A more comprehensive understanding of the rupture kinetics of liquid marble is instructive for studies in improving the stability of liquid marble. However, the mechanism of rupture of liquid marbles is not clear at present, therefore, this paper addressed this issue by calculating the displacement of particles on the surface of a liquid marble using the DIC (Digital Image Correlation) algorithm. The distribution characteristics of the particles on the surface of the liquid marble and their movement patterns were clarified, the causes of cracks on the marble surface were analyzed, the mechanism of liquid marble rupture was derived, and the effect of volume on rupture kinetics was analyzed. Based on the obtained data, a method was proposed to control the maximum compression that the liquid marble can withstand by spraying different sizes of superhydrophobic coatings. This paper contributes to the study of the stability of liquid marble, allowing its wider application in industrial production.

A pointwise optimal subset selection strategy assisted by shape functions in digital image correlation algorithm

A pointwise optimal subset selection strategy assisted by shape functions in digital image correlation algorithm

Crack branching at low tip speeds: spilling the T

Using the criterion that a crack will extend along the direction of maximum circumferential stress, this paper demonstrates the influence of the coupling between the crack-parallel T-stress and the tip speed on the directional (in)stability of dynamics cracks in brittle materials, i.e., branching, turning, and limiting velocities. The proposed (in)stability criterion evolves within the theory of dynamic fracture: we build on the work of Ramulu and Kobayashi (1983) by introducing a reference distance ahead of the crack-tip to incorporate the contribution of the higher-order terms in the asymptotic solution of the elastic crack-tip fields. The theoretical aspect is first explored, a methodology to numerically (and experimentally) advocate the instability—as a co-action of T-stress and a fast-running crack—is then proposed and validated on Borden et al. (2012)’s branching benchmark. An experimental setup combining Ultra-High-Speed High-Resolution imaging with advanced Digital Image Correlation algorithms and a novel crack-branching inertial impact test enables for never-seen-before quantification of the rich dynamical behaviour of the fracture. This permits the experimental validation of the developed crack (in)stability criterion.

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.

Use of lightweight FFT-based algorithms for remote measurements using DIC

Abrupt collapse events that result in casualties due to failure of load-bearing structures have been reported in recent years. Continuous remote monitoring of these structures, assessing the behavior under operational load, could provide a reliable prevention, as the developing damage manifests itself through a loss of stiffness, and therefore excessive deflections. Digital image correlation (DIC) algorithms based on fast Fourier transform (FFT) were implemented in a small computer unit Raspberry Pi, capable of remote operation in a low-energy demand mode. The unit is fully autonomous, capable of localizing QR code targets and extracting encoded information. This strategy allows us to instantly evaluate displacements of QR codes attached to any surface and send the data to a server. The software was developed in Python, allowing for two modes: the online mode for current data evaluation with information transfer via the MQTT protocol and the offline mode used for retrospective evaluation.

Non-contact type dynamic responses test of wind turbines

The performance analysis of wind turbine systems should be considered when calculating the wind speed relative to the wind turbine structure, and is essential for wind turbine design. Since the conditions are precarious in transient state and the operating environments are challenging, the wind turbine is a complex, multivariate, nonlinear system. This paper presents a novel dynamic response test method for wind turbines based on three-dimensional digital speckle measurement. This method use a real-time speckle image collection of objects in various stages using binocular stereo vision to perform stereo matching of deformation points on object surface. A digital image correlation algorithm is used to rebuild three-dimensional space coordinates of matching points so as to achieve wind turbine dynamic response. A laboratory-scale experimental platform is constructed to test the dynamic response of the wind turbine system. In order to verify the accuracy of the proposed method, a three-dimensional model of a wind turbine is built. With dynamic structure response process adopted to carry out dynamic analysis and compare theoretical results with test results, the results vary by less than 10 %, indicating that the test method presented in the paper is feasible and effective.

Challenges and solutions of environmental scanning electron microscopy characterisation of biomaterials: Application to hygro‐expansion of paper

AbstractMost methodologies to measure the moisture‐induced deformation (hygro‐expansion) of paper microconstituents, including fibres and interfibre bonds, are low resolution or time‐consuming. Hence, here, a novel method is proposed and validated to measure high‐resolution full‐field strain maps of paper microconstituents during hygro‐expansion, based on environmental scanning electron microscopy (ESEM). To this end, a novel climate stage enables accurate control of the relative humidity (RH) near the specimen in the ESEM from 0%–100%. The fibre surface, which is decorated a priori with a microparticle pattern, is captured during RH change. Subsequently, correlating the fibre surface using a dedicated global digital image correlation algorithm enables high‐resolution hygro‐expansion strain maps. Method optimisation involved performing contrast enhancement, scan‐correction to reduce ESEM artefacts and a background correction, resulting in a strain resolution of . Method validation revealed that the fibres' crystallinity is affected by the electron beam, even for minimal invasive electron beam settings. Interestingly, however, the fibres consistently exhibit conventional hygro‐expansion behaviour during the drying slopes. Using the optimised procedure, hygro‐expansion characterisation of two interfibre bonds and four interfibre bond cross‐sections revealed the competition between the low longitudinal and large transverse fibre hygro‐expansion in the bonded area.

Detecting Recent Dynamics in Large-Scale Landslides via the Digital Image Correlation of Airborne Optic and LiDAR Datasets: Test Sites in South Tyrol (Italy)

Large-scale slow-moving deep-seated landslides are complex and potentially highly damaging phenomena. The detection of their dynamics in terms of displacement rate distribution is therefore a key point to achieve a better understanding of their behavior and support risk management. Due to their large dimensions, ranging from 1.5 to almost 4 km2, in situ monitoring is generally integrated using satellite and airborne remote sensing techniques. In the framework of the EFRE-FESR SoLoMon project, three test-sites located in the Autonomous Province of Bolzano (Italy) were selected for testing the possibility of retrieving significant slope displacement data from the analysis of multi-temporal airborne optic and light detection and ranging (LiDAR) surveys with digital image correlation (DIC) algorithms such as normalized cross-correlation (NCC) and phase correlation (PC). The test-sites were selected for a number of reasons: they are relevant in terms of hazard and risk; they are representative of different type of slope movements (earth-slides, deep seated gravitational slope Deformation and rockslides), and different rates of displacement (from few cm/years to some m/years); and they have been mapped and monitored with ground-based systems for many years (DIC results can be validated both qualitatively and quantitatively). Specifically, NCC and PC algorithms were applied to high-resolution (5 to 25 cm/px) airborne optic and LiDAR-derived datasets (such as hillshade and slope maps computed from digital terrain models) acquired during the 2019–2021 period. Qualitative and quantitative validation was performed based on periodic GNSS surveys as well as on manual homologous point tracking. The displacement maps highlight that both DIC algorithms succeed in identifying and quantifying slope movements of multi-pixel magnitude in non-densely vegetated areas, while they struggle to quantify displacement patterns in areas characterized by movements of sub-pixel magnitude, especially if densely vegetated. Nonetheless, in all three landslides, they proved to be able to differentiate stable and active parts at the slope scale, thus representing a useful integration of punctual ground-based monitoring systems.

A stable and effective calibration method for defocused cameras using synthetic speckle patterns

Well-focused and sharp target images are essential in traditional calibration, but they generally cause difficulty and inconvenience in image acquisition in practical applications. To address this problem, a stable and effective calibration method for defocused cameras is proposed in this study. Firstly, two speckle patterns are created, one of which has control points to estimate the initial value while the other, used for point pair match registration, is without control points. They are subsequently displayed on a fixed monitor and captured at each camera pose. Secondly, the initial guess for the control points is estimated using the proposed method. The retrieval of query points can then be done with high accuracy using the digital image correlation algorithm. Finally, all the calibration parameters, including lens distortion, are calculated using the plane calibration algorithm. The experiment in this study demonstrates the practicality and effectiveness of the proposed method. The accuracy and precision were quantitatively evaluated by the mean reprojection error, which was 0.057 pixels.