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首页> 外文期刊>Optical engineering >Crack recognition and reconstruction with coarse-fine discontinuous digital image correlation
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Crack recognition and reconstruction with coarse-fine discontinuous digital image correlation

机译：粗细不连续数字图像相关的裂纹识别与重建

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摘要

The recognition of structural cracks and reconstruction of displacement fields around cracks are challenging tasks in engineering. By improving the standard digital image correlation (DIC) method and applying it in measuring the discontinuity of cracks, this study presents a coarse-fine search strategy based on a discontinuous DIC for rapid crack recognition and accurate reconstruction of the displacement fields. The technique introduces a split-subset model with a vector that represents the direction of crack opening to overcome the limitation of the standard DIC in analyzing discontinuous areas. A specially designed coarse-fine search strategy is applied to support the calculation model for achieving higher accuracy. The proposed approach is validated using numerically synthesized crack images as well as images obtained from notch tensile experiments in the laboratory. The results show that the proposed method can recognize the crack faces; in addition, it works well for reconstructing the displacement fields of both continuous and discontinuous (cracked) areas with average absolute errors of approximately 0.02. The proposed technique is also valid for slightly noised images.
机译：结构裂缝的识别和裂缝周围位移场的重建是工程上的艰巨任务。通过改进标准数字图像相关性（DIC）方法并将其应用于裂缝不连续性的测量，本研究提出了一种基于不连续DIC的粗细搜索策略，以快速识别裂缝并精确重建位移场。该技术引入了具有向量的裂痕子集模型，该向量表示裂纹的打开方向，从而克服了标准DIC在分析不连续区域时的局限性。专门设计的粗精细搜索策略用于支持计算模型，以实现更高的准确性。使用数值合成的裂纹图像以及从实验室中的缺口拉伸实验获得的图像验证了该方法的有效性。结果表明，该方法能够识别出裂纹面。另外，它对于重建平均绝对误差约为0.02的连续和不连续（裂纹）区域的位移场也很有效。所提出的技术对于轻微噪点的图像也是有效的。

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