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New levels of high angular resolution EBSD performance via inverse compositional Gauss-Newton based digital image correlation

机译:基于逆成分高斯 - 牛顿的数字图像相关性的新型高角度分辨率EBSD性能

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Conventional high angular resolution electron backscatter diffraction (HREBSD) uses cross-correlation to track features between diffraction patterns, which are then related to the relative elastic strain and misorientation between the diffracting volumes of material. This paper adapts inverse compositional Gauss Newton (ICGN) digital image correlation (DIC) to be compatible with HREBSD. ICGN-based works by efficiently tracking not just the shift in features, but also the change in their shape. Modeling a shape change as well as a shift results in greater accuracy. This method, ICGN-based HREBSD, is applied to a simulated data set, and its performance is compared to conventional cross-correlation HREBSD, and cross-correlation HREBSD with remapping. ICGN-based HREBSD is shown to have about half the strain error of the best cross-correlation method with a comparable computation time.
机译:常规的高角度分辨率电子反向散射衍射(HreBSD)使用互相关与衍射图案之间的特征,然后与衍射体积的相对弹性应变和误导性有关。 本文适应逆成分高斯牛顿(ICGN)数字图像相关(DIC)与HREBSD兼容。 基于ICGN的作品,通过有效跟踪不仅仅是在特征中的转变,还可以改变它们的形状。 模拟形状变化以及转变导致更高的准确性。 该方法,基于ICGN的HREBSD应用于模拟数据集,并将其性能与传统的互相关HREBSD进行比较,以及具有重新映射的互相关HREBSD。 基于ICGN的HREBSD显示了具有相当计算时间的最佳互相关方法的大约一半的应变误差。

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