Single-step scanner-based digital image correlation (SB-DIC) method for large deformation mapping in rubber

The incremental digital image correlation (DIC) method has been applied in the past to determine strain in large deformation materials like rubber. This method is, however, prone to cumulative errors since the total displacement is determined by combining the displacements in numerous stages of the deformation. In this work, a method of mapping large strains in rubber using DIC in a single-step without the need for a series of deformation images is proposed. The reference subsets were deformed using deformation factors obtained from the fitted mean stress-axial stretch ratio curve obtained experimentally and the theoretical Poisson function. The deformed reference subsets were then correlated with the deformed image after loading. The recently developed scanner-based digital image correlation (SB-DIC) method was applied on dumbbell rubber specimens to obtain the in-plane displacement fields up to 350% axial strain. Comparison of the mean axial strains determined from the single-step SB-DIC method with those from the incremental SB-DIC method showed an average difference of 4.7%. Two rectangular rubber specimens containing circular and square holes were deformed and analysed using the proposed method. The resultant strain maps from the single-step SB-DIC method were compared with the results of finite element modeling (FEM). The comparison shows that the proposed single-step SB-DIC method can be used to map the strain distribution accurately in large deformation materials like rubber at much shorter time compared to the incremental DIC method.     

A novel speckle pattern—Adaptive digital image correlation approach with robust strain calculation

Digital image correlation (DIC) has seen widespread acceptance and usage as a non-contact method for the determination of full-field displacements and strains in experimental mechanics. The advances of imaging hardware in the last decades led to high resolution and speed cameras being more affordable than in the past making large amounts of data image available for typical DIC experimental scenarios. The work presented in this paper is aimed at maximizing both the accuracy and speed of DIC methods when employed with such images. A low-level framework for speckle image partitioning which replaces regularly shaped blocks with image-adaptive cells in the displacement calculation is introduced. The Newton-Raphson DIC method is modified to use the image pixels of the cells and to perform adaptive regularization to increase the spatial consistency of the displacements. Furthermore, a novel robust framework for strain calculation based also on the Newton-Raphson algorithm is introduced. The proposed methods are evaluated in five experimental scenarios, out of which four use numerically deformed images and one uses real experimental data. Results indicate that, as the desired strain density increases, significant computational gains can be obtained while maintaining or improving accuracy and rigid-body rotation sensitivity.     

Elasticity effects on domain coarsening of the lamellar-gyroid transition observed in a nonionic surfactant system

The coarsening process of the gyroid phase of a nonionic surfactant system is investigated by time resolved small angle neutron scattering (SANS) and small angle neutron Laue diffraction techniques. The time evolution of SANS patterns shows anomalous coarsening of the gyroid domains. The observed Laue spot from a gyroid domain becomes elongated along the radial direction with the elapse of time and at a certain time the elongated spot is split into two spots. The results can be interpreted as follows. During the coarsening process, mismatch of the lattice orientation at the domain boundary brings strong stress to the gyroid domain, resulting in the distortion of the domain. The stored stress in the domain finally brings splitting of the gyroid domain. The elastic and fragile nature of the gyroid domains composed of the "soft matter" is responsible for the anomalous coarsening.     

Study of optimal subset size in digital image correlation of speckle pattern images

This paper investigates the effect of subset size, associated with image pattern quality and subset displacement functions, on the accuracy of deformation measurements by digital image correlation(DIC). A concept of subset entropy is introduced in this work to quantify the subset image pattern quality for DIC analysis and its effectiveness was demonstrated by experimental studies. By employing white-light images with almost uniform subset entropy and first-order displacement functions, the effect of subset size on DIC analysis was investigated for the deformation cases of translation, uniform deformation, and simulated quadratic deformation, respectively. The results show that the chosen subset size must be large enough for precise displacement measurements when subset displacement functions match underlying actual deformation. On the other hand, optimal subset size in DIC for nonhomgeneous deformation measurements appears as a result of a tradeoff between the influence of random errors and systematic errors.     

用差矢法标定高级劳厄点

对于电子衍射谱的高级劳厄带斑点标定,提出一种新的方法。直接通过测定亮衍射斑的点间距和向量合成来标定高级劳厄带第一个衍射斑的指数,进一步导出最靠近入射斑和其它的斑点指数。 关键词：     

Energy resolution of the CdTe‐XPAD detector: calibration and potential for Laue diffraction measurements on protein crystals

The XPAD3S‐CdTe, a CdTe photon‐counting pixel array detector, has been used to measure the energy and the intensity of the white‐beam diffraction from a lysozyme crystal. A method was developed to calibrate the detector in terms of energy, allowing incident photon energy measurement to high resolution (approximately 140 eV), opening up new possibilities in energy‐resolved X‐ray diffraction. In order to demonstrate this, Laue diffraction experiments were performed on the bending‐magnet beamline METROLOGIE at Synchrotron SOLEIL. The X‐ray energy spectra of diffracted spots were deduced from the indexed Laue patterns collected with an imaging‐plate detector and then measured with both the XPAD3S‐CdTe and the XPAD3S‐Si, a silicon photon‐counting pixel array detector. The predicted and measured energy of selected diffraction spots are in good agreement, demonstrating the reliability of the calibration method. These results open up the way to direct unit‐cell parameter determination and the measurement of high‐quality Laue data even at low resolution. Based on the success of these measurements, potential applications in X‐ray diffraction opened up by this type of technology are discussed.     

Assessment of measuring errors in DIC using deformation fields generated by plastic FEA

In this article, systematic errors that arise from different implementations of digital image correlation (DIC) techniques are analyzed. In particular, we investigate the influence of the adopted correlation function, the interpolation order, the shape function and the subset size on the derived displacements. These errors are estimated using numerically deformed images that were obtained by imposing finite element (FE) displacement fields on an undeformed image yielding plastic deformation of the specimen. This FE procedure simulates realistic experimental heterogeneous deformations at various load steps. It is shown that DIC is able to reproduce these displacements up to a satisfactory level if conscious choices in the above-mentioned implementations are made.     

Incremental calculation for large deformation measurement using reliability-guided digital image correlation

Conventional digital image correlation (DIC) technique using a fixed reference image provides high-accuracy measurements but normally fails when serious decorrelation effect occurs in the deformed images due to large deformation, serious illumination fluctuations or other reasons. In this paper, an incremental reliability-guided digital image correlation (RG-DIC) technique, by combining the recently developed RG-DIC technique and an automatic reference image updating scheme, is proposed for large deformation measurement. In the incremental RG-DIC technique, a seed point is defined in the original reference image and searched in the deformed images, if the estimated correlation coefficient is larger than a preset threshold, which means no serious decorrelation effect exists in the deformed image, the RG-DIC technique is used to continue correlation analysis to obtain full-field displacements. Otherwise, the image recorded just before the current deformed image is chosen as an updated reference image to proceed with correlation analysis. Afterwards, the incremental displacements extracted by comparing the current deformed image and the updated reference image can be cumulated to determine the overall deformation. The effectiveness of the proposed technique is demonstrated by retrieving the full-field deformation of a foam sample subjected to large compressive deformation.     

Large deformation measurement scheme for 3D digital image correlation method

Difficulties often arise for digital image correlation (DIC) technique when serious de-correlation occurs between the reference image and the deformed image due to large deformation. An updating reference image scheme could be employed to deal with large deformation situation, however that will introduce accumulated errors. A large deformation measurement scheme, combining improved coarse search method and updating reference image scheme, is proposed in this paper. For a series of deformation images, the correlation calculation begins with a seed point and spreads out. An improved coarse search method is developed to calculate the initial correlation parameters for the seed point, which guarantees that the correlation calculation can be carried out successfully even in large deformation situation. Only for extremely large deformation, the reference image is updated. Using this method, not only extremely large deformation can be measured successfully but also the accumulated error could be controlled. A polymer material tensile test and a foam compression test are used to verify the proposed scheme. Experimental results show that up to 450% tensile deformation and 83% compression deformation can be measured successfully.     

提高多光源汇聚光斑中心定位精度的形态学滤波方法

在激光指令传输中,为形成较大的光覆盖区域并增大光源的作用距离,将多个特性相同的激光器矩阵排列,构成组合光源。针对点阵多激光管光源在开放环境下成像光斑具有多个光能中心的特点,采用形态学滤波中的开启、闭合运算,去除背景噪声斑点,平滑光斑内部的小光斑叠加和干涉造成的不规则条、孔,使得能以简化的分割和定位算法,快速获得接近实际的完整光斑边界,光斑中心定位精度的均方差不大于1.2%。该方法能快速、高精度定位这种叠加光斑的中心,为远距离激光对准和测控提供了可靠的精度和时效保证。     

Shortcut in DIC error assessment induced by image interpolation used for subpixel shifting

In order to characterize errors of Digital Image Correlation (DIC) algorithms, sets of virtual images are often generated from a reference image by in-plane sub-pixel translations. This leads to the determination of the well-known S-shaped bias error curves and their corresponding random error curves. As images are usually shifted by using interpolation schemes similar to those used in DIC algorithms, the question of the possible bias in the quantification of measurement uncertainties of DIC softwares is raised and constitutes the main problematic of this paper. In this collaborative work, synthetic numerically shifted images are built from two methods: one based on interpolations of the reference image and the other based on the transformation of an analytic texture function. Images are analyzed using an in-house subset-based DIC software and results are compared and discussed. The effect of image noise is also highlighted. The main result is that the a priori choices to numerically shift the reference image modify DIC results and may lead to wrong conclusions in terms of DIC error assessment.     

A fast digital image correlation method for deformation measurement

Fast and high-accuracy deformation analysis using digital image correlation (DIC) has been increasingly important and highly demanded in recent years. In literature, the DIC method using the Newton-Rapshon (NR) algorithm has been considered as a gold standard for accurate sub-pixel displacement tracking, as it is insensitive to the relative deformation and rotation of the target subset and thus provides highest sub-pixel registration accuracy and widest applicability. A significant drawback of conventional NR-algorithm-based DIC method, however, is its extremely huge computational expense. In this paper, a fast DIC method is proposed deformation measurement by effectively eliminating the repeating redundant calculations involved in the conventional NR-algorithm-based DIC method. Specifically, a reliability-guided displacement scanning strategy is employed to avoid time-consuming integer-pixel displacement searching for each calculation point, and a pre-computed global interpolation coefficient look-up table is utilized to entirely eliminate repetitive interpolation calculation at sub-pixel locations. With these two approaches, the proposed fast DIC method substantially increases the calculation efficiency of the traditional NR-algorithm-based DIC method. The performance of proposed fast DIC method is carefully tested on real experimental images using various calculation parameters. Results reveal that the computational speed of the present fast DIC is about 120-200 times faster than that of the traditional method, without any loss of its measurement accuracy     

Measuring grain rotation at the nanoscale

In this paper, we introduced a method to measure grain rotation of nanomaterials under external stress using a high pressure diamond anvil cell and the Laue microdiffraction technique at a synchrotron facility. We used tungsten carbide marker crystals to investigate grain rotation activities of 3 and 500?nm nickel media. Our results show that the grain rotation of 3 and 500?nm nickel nanocrystals increase with pressure and finally rotation of 500?nm nickel tends to stop at a lower pressure/stress level than 3?nm nickel. 3?nm nickel nanocrystals show a higher rotation magnitude than 500?nm nickel nanocrystals. Our measurements show an effective method to study the grain rotation of nanomaterials especially in ultrafine nanocrystals.     

Gaussian pre-filtering for uncertainty minimization in digital image correlation using numerically-designed speckle patterns

This paper discusses the effect of pre-processing image blurring on the uncertainty of two-dimensional digital image correlation (DIC) measurements for the specific case of numerically-designed speckle patterns having particles with well-defined and consistent shape, size and spacing. Such patterns are more suitable for large measurement surfaces on large-scale specimens than traditional spray-painted random patterns without well-defined particles. The methodology consists of numerical simulations where Gaussian digital filters with varying standard deviation are applied to a reference speckle pattern. To simplify the pattern application process for large areas and increase contrast to reduce measurement uncertainty, the speckle shape, mean size and on-center spacing were selected to be representative of numerically-designed patterns that can be applied on large surfaces through different techniques (e.g., spray-painting through stencils). Such “designer patterns” are characterized by well-defined regions of non-zero frequency content and non-zero peaks, and are fundamentally different from typical spray-painted patterns whose frequency content exhibits near-zero peaks. The effect of blurring filters is examined for constant, linear, quadratic and cubic displacement fields. Maximum strains between ±250 and ±20,000 µε are simulated, thus covering a relevant range for structural materials subjected to service and ultimate stresses. The robustness of the simulation procedure is verified experimentally using a physical speckle pattern subjected to constant displacements. The stability of the relation between standard deviation of the Gaussian filter and measurement uncertainty is assessed for linear displacement fields at varying image noise levels, subset size, and frequency content of the speckle pattern. It is shown that bias error as well as measurement uncertainty are minimized through Gaussian pre-filtering. This finding does not apply to typical spray-painted patterns without well-defined particles, for which image blurring is only beneficial in reducing bias errors.     

Comparison of subset-based local and FE-based global digital image correlation: Theoretical error analysis and validation

Subset-based local and finite-element-based (FE-based) global digital image correlation (DIC) approaches are the two primary image matching algorithms widely used for full-field displacement mapping. Very recently, the performances of these different DIC approaches have been experimentally investigated using numerical and real-world experimental tests. The results have shown that in typical cases, where the subset (element) size is no less than a few pixels and the local deformation within a subset (element) can be well approximated by the adopted shape functions, the subset-based local DIC outperforms FE-based global DIC approaches because the former provides slightly smaller root-mean-square errors and offers much higher computation efficiency. Here we investigate the theoretical origin and lay a solid theoretical basis for the previous comparison. We assume that systematic errors due to imperfect intensity interpolation and undermatched shape functions are negligibly small, and perform a theoretical analysis of the random errors or standard deviation (SD) errors in the displacements measured by two local DIC approaches (i.e., a subset-based local DIC and an element-based local DIC) and two FE-based global DIC approaches (i.e., Q4-DIC and Q8-DIC). The equations that govern the random errors in the displacements measured by these local and global DIC approaches are theoretically derived. The correctness of the theoretically predicted SD errors is validated through numerical translation tests under various noise levels. We demonstrate that the SD errors induced by the Q4-element-based local DIC, the global Q4-DIC and the global Q8-DIC are 4, 1.8–2.2 and 1.2–1.6 times greater, respectively, than that associated with the subset-based local DIC, which is consistent with our conclusions from previous work.     

Optimization for high precision Shack-Hartmann wavefront sensor

A comprehensive noise model about digital camera which is a main component of SHWFS is constructed, including the readout noise, the photon shot noise, the quantization noise and the response un-uniformity. Based on the noise model, the spot centroid errors caused by each kind of noise are analyzed, respectively. And then the synthetic error from all the noise is calculated. The result demonstrates that the limit of the spot centroid accuracy is 1% pixels. At last, the crossing error caused by the high order diffraction spots is analyzed. It is approximately proportional to the secondary spots number. So the structure of the microlens array must be optimized together with the digital camera when designing SHWFS.     

基于人眼视觉特性的火炮内膛图像增强方法

为了提高窥膛图像的观测效果,减小背景和噪声对目标图像的模糊度,根据图像特点提出了一种基于人眼视觉特性的图像增强新方法.该方法根据目标图像与背景、噪声图像特性的差异来进行不同的处理,使待测的疵病图像相对增强,目标图像突出,便于人眼观察.     

The RATIO method for time‐resolved Laue crystallography

A RATIO method for analysis of intensity changes in time‐resolved pump–probe Laue diffraction experiments is described. The method eliminates the need for scaling the data with a wavelength curve representing the spectral distribution of the source and removes the effect of possible anisotropic absorption. It does not require relative scaling of series of frames and removes errors due to all but very short term fluctuations in the synchrotron beam.     

The LaueUtil toolkit for Laue photocrystallography. II. Spot finding and integration

A spot‐integration method is described which does not require prior indexing of the reflections. It is based on statistical analysis of the values from each of the pixels on successive frames, followed for each frame by morphological analysis to identify clusters of high value pixels which form an appropriate mask corresponding to a reflection peak. The method does not require prior assumptions such as fitting of a profile or definition of an integration box. The results are compared with those of the seed‐skewness method which is based on minimizing the skewness of the intensity distribution within a peak's integration box. Applications in Laue photocrystallography are presented.     

基于双目视觉的车身焊点定位误差补偿研究

在应用机器人对车身点焊质量检测过程中,其焊点的定位精度受到点焊作业质量以及车身制造误差等因素的影响,导致实际焊点与设计值并不重合。针对传统示教无法对焊点定位进行实时补偿的问题,提出基于双目视觉引导机器人的焊点定位策略,并构建基于改进粒子群算法优化的支持向量机回归误差补偿模型,对定位结果进行补偿。在机器人末端安装双目传感器,利用双目定位原理对焊点进行初步定位,并将焊点位置的测量数据与实际数据作为学习样本,利用训练好的误差补偿模型预测系统定位误差,将补偿结果作为纠偏值引导机器人定位焊点。实验结果表明,补偿后的定位精度得到较大提升,验证了该方法的有效性。