非连续数字图像相关方法在裂纹重构中的应用

数字图像相关方法作为一种新的非接触式位移测量方法,在力学工程中有广泛的应用前景,然而受限于标准方法对图像变形的连续性要求,这种高效的测量方法在断裂力学领域的推广受到了限制.为解决这一问题,提出采用引入子区分离数学模型,代替标准方法的连续模型,来对非连续区域进行精确识别和匹配的非连续数字图像相关方法.研究子区被裂纹等非连续分割后原始像素点的位移情况,并引入裂纹张开向量用以表征被分割子区的主区和副区的位移关系;从而建立子区分离模型的数学表达式,并且为所提出的模型设计相应的图像相关算法;然后将所提出的非连续数字图像相关方法应用于重构平板拉伸试验开裂过程中图像的位移.研究结果表明,相比于标准的数字图像相关方法,所提出的非连续数字图像相关方法解决了图像相关法在非连续区域失效的问题,提高了数字图像相关方法对位移测量的正确率,特别是能够准确重构裂纹面及附近的位移场,其测量精度能够达到亚像素级别.     

后验概率算法用于位移场的确定

提出了一种基于贝叶斯最大后验估计算法确定固体表面位移场的方法。在图像处理过程中，把位移看作随机变量，首先建立贝叶斯模型，对变形前数字图像中的一个像素点，选定变形前后两幅数字图像中对应的圆形子区，将两子区所对应的所有可能位移逐一代入贝叶斯后验概率公式进行计算，使后验概率最大的位移值就是所求该点的位移。在得到整像素位移之后，引入亚像素重建技术，确定图像的精确位移场。本文通过计算机数字模拟实验和实物标准位移实验，验证了该方法的可行性，并得到了0．02pixel的位移测量精度。     

基于退相关DIC的疲劳裂纹全局动态测量方法

工程材料和结构在反复荷载长期作用下容易发生疲劳开裂, 疲劳裂纹测量对于开展科学试验研究和工程问题分析都至关重要, 但现有方法无法实现高精度的疲劳裂纹全局动态测量. 本文基于数字图像相关(digital image correlation, DIC)技术, 合理利用DIC的退相关效应, 提出一种疲劳裂纹全局动态测量及可视化方法. 该方法首先在相机采集得到的裂纹图像内, 建立具备拓扑关系的目标点云结构, 并运用DIC亚像素算法得到裂纹区域位移场, 再基于零均值归一化互相关(zero-mean normalized cross correlation, ZNCC)计算结果剔除退相关的DIC目标点(灭点). 进一步通过“三生点”算法提取得到裂纹离散边界, 并采用最小二乘法将离散边界拟合为连续裂纹边界, 实现裂纹形态的几何重构, 最终自动计算得到裂纹长度和宽度的动态变化过程. 该方法原理清晰、理论简单, 易于实现. 开展数值模拟和钢节点疲劳试验, 对相关算法和图像采集参数进行了验证, 结果表明本文方法对疲劳裂纹边界的数字化重构误差在0.5个像素内, 基于重构结果计算得到的裂纹长度和宽度误差分别为0.46像素和0.08像素(类同于0.06 mm和0.01 mm), 并成功实现了对疲劳试验裂纹扩展形态的精细化动态测量及可视化. 研究成果证明了DIC技术用于疲劳裂纹全局动态测量及可视化的有效性, 并在测量精度、效率、成本等方面具有显著优势, 可在实验室测量和工程现场测试中推广应用.      

基于主应变场的混凝土全表面开裂特征实时测量与分析

测量裂纹的扩展过程对于揭示混凝土结构的破坏机理和评价其力学性能十分重要. 本文提出了一种基于混凝土表面变形场的裂纹定位和宽度测量方法, 首先基于多相机数字图像相关方法得到混凝土试件表面的高分辨变形场, 发现开裂引起的位移梯度使裂纹附近的虚主应变场明显区别于未开裂处, 且主应变场在裂纹法线方向近似高斯分布. 借鉴在激光条纹中心线定位中广泛采用的Steger算法思想, 提出了基于主应变场的裂纹定位方法, 并将裂纹两侧位于法线上的面内位移向量做差沿裂纹法线方向上的投影为Ⅰ型裂纹宽度, 沿裂纹切线方向上的投影为Ⅱ型裂纹宽度, 最终得到了裂纹每一点的位置和宽度. 利用高精度平移台设计了模拟裂纹扩展的实验, 以验证Ⅰ型裂纹宽度的测量精度. 实验结果表明: 裂纹宽度的测量误差在0.010 ~ 0.017像素之间, 与理论预测相符; 测量误差的标准差在0.006 ~ 0.008像素之间, 测量结果比较稳定. 在同等分辨率下, 本文方法的测量精度优于基于图像的裂纹测量方法. 本文提出的方法可以全自动、实时地测量裂纹扩展, 为混凝土实验提供了一种可靠、精确的全场裂纹测量手段.      

数学网格和物理网格分离的有限单元法(II):粘聚裂纹扩展问题中的应用

强化有限单元法将物理网格与数学网格分离开来,可以方便地描述非连续变形;粘聚区域模型是模拟断裂过程区作用最简单有效的方法,且可以避免裂纹尖端的应力奇异性.本文以平面问题为例,将强化有限单元法与粘聚区域模型相结合,利用富集数学节点描述任意粘聚裂纹扩展过程中的非连续变形问题,提出了裂纹扩展过程中数学节点富集和数学单元定义的方法.本文还导出了与平面4～8节点平面等参单元对应的8～16节点粘聚裂纹单元列武.最后,通过三点弯梁的裂纹扩展过程模拟验证了本文提出的粘聚裂纹扩展模拟方法的有效性.     

数字图像相关方法中匹配及过匹配形函数的误差分析

基于图像子区的数字图像相关方法需采用合适的形函数来近似目标图像子区的真实变形。由于实际测量时目标子区的局部变形往往是未知的,实际采用的不同阶次(零阶、一阶和二阶)的形函数不可避免地产生误匹配(欠匹配和过匹配)问题,从而引入位移测量的系统或随机误差。尽管由欠匹配形函数引起的系统误差已被充分认识,由过匹配形函数引起的位移误差仍缺少理论解释。本文首先推导出采用一阶和二阶形函数的数字图像相关方法的随机误差理论公式,随后采用一系列数值实验验证了理论公式的准确性。结果显示:过匹配形函数不会引入额外的系统误差,但会增加随机误差,且二阶形函数的随机误差是一阶形函数的二倍。考虑到由欠匹配一阶形函数引入的系统误差往往远大于过匹配二阶形函数的随机误差,因此在未能确知变形的情况下,推荐使用二阶形函数。     

基于Haar小波变换的位移场测量方法

本文提出了一种应用小波变换对固体表面位移场进行测量的新方法，在图像分析时，用各点属于不同尺度的小波变换系数来表征该点周围的子区。将试件表面位移前后的两幅数字图像进行小波变换，通过变形前后两幅图像小波变换系数之间的相互匹配，使位移前后两幅图中的子区对应起来，从而确定图像的位移场。本文应用Haar小波变换进行了计算机模拟实验和实物位移实验。引入亚像素技术，获得了0．02的位移测量精度。     

钢纤维增强混凝土的断裂破坏研究

在钢纤维增强混凝土的断裂力学性能的实验研究中,利用数字图像相关技术对素水泥砂浆试件和钢纤维增强水泥砂浆试件进行裂纹尖端的位移场测量,求解不同纤维分布情况下的应力强度因子从而进行增强性能的分析比较.对于单纤维桥联增强的情况,实验结果与Carpinteri的模型计算结果进行了分析比较,证明这种图像和数据处理方法对裂纹尖端的纤维位增强特性分析是有效可行的.     

数字图像相关中亚像素位移测量算法的研究

为提高位移测量精度而提出的各种亚像素位移测量算法被认为是数字图像相关方法 中的关键技术之一，详细了解已有各算法的性能无疑具有实际意义. 总结文献中3种 最常用的亚像素位移测量算法，首先用无噪声的计算机仿真散斑图对各算法的性能从计算精 度和计算效率两个方面进行了比较研究，并用实际实验图片对其性能做进一步的研究，结果 显示在图像子区大小相同的情况下，基于空域相关函数迭代的牛顿-拉普森方法计算结果最 为精确、稳定.     

一种基于DIC测量单边缺口拉伸试件CTOD阻力曲线的简便方法

针对测量单边缺口拉伸(SENT)试样的裂纹尖端张口位移(CTOD)阻力曲线时,延性裂纹扩展量的计算过于复杂的问题,提出了一种由数字图像相关技术(DIC)计算的变形场来确定裂纹尖端位置,并快速推算延性裂纹扩展量的方法。该方法首先在缺口和裂纹上下方的弹性区域设置两条平行横线;然后通过两条横线间的位移差构建曲线,曲线变化幅度的临界点即为裂纹端部的位置;根据临界点位置计算裂纹扩展量,最后测量CTOD并构建阻力曲线。将本文方法与另一种通过DIC测量SENT试样CTOD阻力曲线的方法进行对比,结果表明本文方法经过简便的计算后拟合的阻力曲线效果更好。     

A Novel “Subset Splitting” Procedure for Digital Image Correlation on Discontinuous Displacement Fields

Digital Image Correlation (DIC) is an easy to use yet powerful approach to measure displacement and strain fields. While the method is robust and accurate for a variety of applications, standard DIC returns large error and poor correlation quality near displacement discontinuities such as cracks or shear bands. This occurs because the subsets used for correlation can only capture continuous deformations from the reference to the deformed image. As a result the regions around discontinuities are typically removed from the area of interest, before or after analysis. Here, a novel approach is proposed which enables the subset to split in two sections when a discontinuity is detected. This method enables the measurement of “displacement jumps”, and also of displacements and strains right by the discontinuity (for example a crack profile or residual strains in the wake). The method is validated on digitally created images based on mode I and mode II asymptotic displacement fields, for both sub-pixel and super-pixel crack opening displacements. Finally, an actual fracture experiment on a high density polyethylene (HDPE) specimen demonstrates the robustness of the method on actual images. Compared to other methods capable of handling discontinuities, this novel “subset-splitting” procedure offers the advantage of being a direct extension of the now popular standard DIC, and can therefore be implemented as an “upgrade” to that method.     

Direct Extraction of Cohesive Fracture Properties from Digital Image Correlation: A Hybrid Inverse Technique

The accuracy of an adopted cohesive zone model (CZM) can affect the simulated fracture response significantly. The CZM has been usually obtained using global experimental response, e.g., load versus either crack opening displacement or load-line displacement. Apparently, deduction of a local material property from a global response does not provide full confidence of the adopted model. The difficulties are: (1) fundamentally, stress cannot be measured directly and the cohesive stress distribution is non-uniform; (2) accurate measurement of the full crack profile (crack opening displacement at every point) is experimentally difficult to obtain. An attractive feature of digital image correlation (DIC) is that it allows relatively accurate measurement of the whole displacement field on a flat surface. It has been utilized to measure the mode I traction-separation relation. A hybrid inverse method based on combined use of DIC and finite element method is used in this study to compute the cohesive properties of a ductile adhesive, Devcon Plastic Welder II, and a quasi-brittle plastic, G-10/FR4 Garolite. Fracture tests were conducted on single edge-notched beam specimens (SENB) under four-point bending. A full-field DIC algorithm was employed to compute the smooth and continuous displacement field, which is then used as input to a finite element model for inverse analysis through an optimization procedure. The unknown CZM is constructed using a flexible B-spline without any “a priori” assumption on the shape. The inversely computed CZMs for both materials yield consistent results. Finally, the computed CZMs are verified through fracture simulation, which shows good experimental agreement.     

数字图像相关方法在桥梁裂缝变形监测中的应用

本文结合工程实际背景分析了数字图像相关方法应用在桥梁裂缝变形监测中的可行性及优越性。根据桥梁裂缝变形的特点采用数字图像处理技术中的位移梯度法进行所选区域的相关匹配搜索并对相关系数的计算公式加以改进。使实验过程得以简化。计算结果全场化、直观化。本文对数字图像处理软件的测量精度和在实际测量中的测试误差进行了分析和研究。证明该软件能够更加精确地测定裂缝在各种荷载作用下的变形量值．实际的桥梁测试也验证了该方法的可行性和优越性。若图像记录设备的分辨率是12．47pixel／mm(0．0802ram／pixel)。本文所涉及到的桥梁裂缝边缘的位移测试精度为0．000802mm。     

扩展数字图像相关方法中裂尖位移函数的表征研究

探寻适用于扩展数字图像相关方法(X-DIC)的裂纹尖端位移函数,对于提高该方法在裂尖测试精度方面具有重要意义。本文基于断裂力学裂纹尖端位移场函数,进行主导项影响分析,并探究裂尖位移函数中各项及其组合项对位移场表征的贡献程度及对测试精度的影响。通过对I型、II型及混合型裂纹进行测试,发现各项及其组合项在不同裂纹类型测试中的影响有着较大区别,从而得出在X-DIC测试计算中影响裂尖位移场表征的主导项。最后,应用上述研究成果对某航空超硬铝合金的单边裂纹进行拉伸测试。     

Fast, Robust and Accurate Digital Image Correlation Calculation Without Redundant Computations

High-efficiency and high-accuracy deformation analysis using digital image correlation (DIC) has become increasingly important in recent years, considering the ongoing trend of using higher resolution digital cameras and common requirement of processing a large sequence of images recorded in a dynamic testing. In this work, to eliminate the redundant computations involved in conventional DIC method using forward additive matching strategy and classic Newton–Raphson (FA-NR) algorithm without sacrificing its sub-pixel registration accuracy, we proposed an equivalent but more efficient DIC method by combining inverse compositional matching strategy and Gauss-Newton (IC-GN) algorithm for fast, robust and accurate full-field displacement measurement. To this purpose, first, an efficient IC-GN algorithm, without the need of re-evaluating and inverting Hessian matrix in each iteration, is introduced to optimize the robust zero-mean normalized sum of squared difference (ZNSSD) criterion to determine the desired deformation parameters of each interrogated subset. Then, an improved reliability-guided displacement tracking strategy is employed to achieve further speed advantage by automatically providing accurate and complete initial guess of deformation for the IC-GN algorithm implemented on each calculation point. Finally, an easy-to-implement interpolation coefficient look-up table approach is employed to avoid the repeated calculation of bicubic interpolation at sub-pixel locations. With the above improvements, redundant calculations involved in various procedures (i.e. initial guess of deformation, sub-pixel displacement registration and sub-pixel intensity interpolation) of conventional DIC method are entirely eliminated. The registration accuracy and computational efficiency of the proposed DIC method are carefully tested using numerical experiments and real experimental images. Experimental results verify that the proposed DIC method using IC-GN algorithm and the existing DIC method using classic FA-NR algorithm generate similar results, but the former is about three to five times faster. The proposed reliability-guided IC-GN algorithm is expected to be a new standard full-field displacement tracking algorithm in DIC.     

Deformation measurements by digital image correlation: Implementation of a second-order displacement gradient

This paper outlines the procedure for refining the digital image correlation (DIC) method by implementing a second-order approximation of the displacement gradients. The second-order approximation allows the DIC method to directly measure both the first- and second-order displacement gradients resulting from nonlinear deformation. Thirteen unknown parameters, consisting of the components of displacement, the first- and second-order displacement gradients and the gray-scale value offset, are determined through optimization of a correlation coefficient. The previous DIC method assumes that the local deformation in a subset of pixels is represented by a first-order Taylor series approximation for the displacement gradient terms, so actual deformations consisting of higher order displacement gradients tend to distort the infinitesimal strain measurements. By refining the method to measure both the first- and second-order displacement gradients, more accurate strain measurements can be achieved in large-deformation situations where second-order deformations are also present. In most cases, the new refinements allow the DIC method to maintain an accuracy of ±0.0002 for the first-order displacement gradients and to reach ±0.0002 per pixel for the second-order displacement gradients.     

Inverse Estimation of Cohesive Fracture Properties of Asphalt Mixtures Using an Optimization Approach

Tensile cracking in asphalt pavements due to vehicular and thermal loads has become an experimental and numerical research focus in the asphalt materials community. Previous studies have used the discrete element method (DEM) to study asphalt concrete fracture. These studies used trial-and-error to obtain local fracture properties such that the DEM models approximate the experimental load-crack mouth opening displacement response. In the current study, we identify the cohesive fracture properties of asphalt mixtures via a nonlinear optimization method. The method encompasses a comparative investigation of displacement fields obtained using both digital image correlation (DIC) and heterogeneous DEM fracture simulations. The proposed method is applied to two standard fracture test geometries: the single-edge notched beam test, SE(B), under three-point bending, and the disk-shaped compact tension test, DC(T). For each test, the Subset Splitting DIC algorithm is used to determine the displacement field in a predefined region near the notch tip. Then, a given number of DEM simulations are performed on the same specimen. The DEM is used to simulate the fracture of asphalt concrete with a linear softening cohesive contact model, where fracture-related properties (e.g., maximum tensile force and maximum crack opening) are varied within a predefined range. The difference between DIC and DEM displacement fields for each set of fracture parameters is then computed and converted to a continuous function via multivariate Lagrange interpolation. Finally, we use a Newton-like optimization technique to minimize Lagrange multinomials, yielding a set of fracture parameters that minimizes the difference between the DEM and DIC displacement fields. The optimized set of fracture parameters from this nonlinear optimization procedure led to DEM results which are consistent with the experimental results for both SE(B) and DC(T) geometries.     

基于数字图像体相关的物体内部三维位移场分析

在二维数字图像相关算法的基础上,推导了三维数字图像体相关算法,并应用于物体内部的三维位移场分析。用计算机模拟方法对SR-CT重建的物体内部三维图像施加已知变形,对变形前后三维数字图像进行体相关运算,获得三维位移场。在计算亚像素位移时,本文提出了一种三维的基于灰度梯度的算法,给出了梯度函数,阐述了数字模拟三维体相关的计算过程,通过数字模拟实验证明了算法的正确性和可靠性。     

Statistical Analysis of the Effect of Intensity Pattern Noise on the Displacement Measurement Precision of Digital Image Correlation Using Self-correlated Images

This paper discusses the effect of intensity pattern noise on the displacement measurement precision of digital image correlation (DIC). Through mathematical deduction, a formula is presented to estimate the displacement measurement error caused by intensity pattern noise. The resulting formula synthetically reflects the effects of the variance of noise, the intensity variance and the subset size on the displacement measurement precision. To verify the correctness of the resulting formula, two experiments are done. The first one is a real self-correlation experiment, and aims to analyze the effect of the subset size, while the second is a numerical self-correlation experiment, and is to analyze to the effect of the different noise levels. The experimental results are in good agreement with the theoretical predictions. The project is supported by the National Science Foundation of China (10572103).