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An Optical Crack Growth Sensor Using the Digital Sampling Moiré Method

机译:使用数字采样莫尔方法的光学裂纹增长传感器

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摘要

High-accuracy crack growth measurement is crucial for the health assessment of concrete structures. In this work, an optical crack growth sensor using the digital sampling moiré (DSM) method is developed for two-dimensional (2D) crack growth monitoring. The DSM method generates moiré fringes from a single image through digital image processing, and it measures 2D displacements using the phase difference of moiré fringes between motion. Compared with the previous sensors using traditional photogrammetric algorithms such as the normalized cross-correlation (NCC) method, this new DSM-based sensor has several advantages: First, it is of a higher sensitivity and lower computational cost; second, it requires no prior calibration to get accurate 2D displacements which can greatly simplify the practical application for multiple crack monitoring. In addition, it is more robust to the change of imaging distance, which is determined by the height difference between two sides of a concrete crack. These advantages break the limitation of the NCC method and broaden the applicability of the crack growth sensor. These advantages have been verified with one numerical simulation and two laboratory tests.
机译:高精度裂纹扩展测量对于混凝土结构的健康评估至关重要。在这项工作中,开发了一种使用数字采样莫尔条纹(DSM)方法的光学裂纹扩展传感器,用于二维(2D)裂纹扩展监控。 DSM方法通过数字图像处理从单个图像生成莫尔条纹,并使用运动之间的莫尔条纹的相位差来测量2D位移。与以前使用传统摄影测量算法(例如归一化互相关(NCC)方法)的传感器相比,这种基于DSM的新型传感器具有以下优点:第一,灵敏度更高,计算成本更低;其次,它无需事先校准即可获得准确的2D位移,从而可以大大简化多裂纹监测的实际应用。此外,它对成像距离的变化更鲁棒,成像距离的变化取决于混凝土裂缝两侧之间的高度差。这些优点打破了NCC方法的局限性,拓宽了裂纹扩展传感器的适用范围。这些优势已通过一项数值模拟和两项实验室测试得到了验证。

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