Assessment of Digital Image Correlation Measurement Errors: Methodology and Results
Assessment of Digital Image Correlation Measurement Errors: Methodology and Results
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DOI：
10.1007/s11340-008-9204-7
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发表时间：
2009-06-01
影响因子：
2.4
通讯作者：
Wattrisse, B.
中科院分区：
文献类型：
--
作者：
Bornert, M.;Bremand, F.;Wattrisse, B.
数字图像相关（DIC）等光学全场测量方法在实验力学领域的应用越来越广泛，但其计量性能方面的信息仍然缺乏。为了评估DIC技术的性能并为用户提供一些实用规则，法国CNRS研究网络2519的“计量”工作组“MCIMS （Mesures de Champs et Identification en M，canique des Solides /固体力学的全场测量和识别，http://www.ifma.fr/lami/gdr2519）开展了一项合作工作。提出了一种方法来评估构成其主要组成部分的图像处理算法的计量性能，需要对整个测量系统进行全局评估的知识。该研究基于合成散斑图像的位移误差评估。假设一个具有不同频率和幅值的正弦位移场，生成了一系列具有随机图案的合成参考图像和变形图像。流离失所是由基于各种公式的几个DIC包来评估的，并在法国社区使用。将计算得到的位移与实际施加的位移进行了比较，并对误差进行了统计分析。结果表明，总体趋势与实现无关，但与底层算法的假设密切相关。识别了各种误差区域，并讨论了不确定性与算法参数（如子集大小、灰度插值或形状函数）的相关性。
Optical full-field measurement methods such as Digital Image Correlation (DIC) are increasingly used in the field of experimental mechanics, but they still suffer from a lack of information about their metrological performances. To assess the performance of DIC techniques and give some practical rules for users, a collaborative work has been carried out by the Workgroup "Metrology" of the French CNRS research network 2519 "MCIMS (Mesures de Champs et Identification en M,canique des Solides / Full-field measurement and identification in solid mechanics, http://www.ifma.fr/lami/gdr2519. A methodology is proposed to assess the metrological performances of the image processing algorithms that constitute their main component, the knowledge of which being required for a global assessment of the whole measurement system. The study is based on displacement error assessment from synthetic speckle images. Series of synthetic reference and deformed images with random patterns have been generated, assuming a sinusoidal displacement field with various frequencies and amplitudes. Displacements are evaluated by several DIC packages based on various formulations and used in the French community. Evaluated displacements are compared with the exact imposed values and errors are statistically analyzed. Results show general trends rather independent of the implementations but strongly correlated with the assumptions of the underlying algorithms. Various error regimes are identified, for which the dependence of the uncertainty with the parameters of the algorithms, such as subset size, gray level interpolation or shape functions, is discussed.