用于沥青混凝土试验中位移和应变测量的SIFT辅助校正2D-DIC
SIFT-Aided Rectified 2D-DIC for Displacement and Strain Measurements in Asphalt Concrete Testing
AI总结：
针对沥青混凝土2D-DIC测量中相机非垂直导致的误差，提出基于SIFT特征匹配与图像校正的无额外设备方法，并通过合成图像、断裂试验及CrackPropNet验证其精度与实用性。
摘要：
二维数字图像相关（2D-DIC）是一种广泛用于在沥青混凝土（AC）试验期间测量位移和应变的光学技术。只有当相机主轴垂直于平面试样表面时，才能实现准确的二维DIC测量。然而，由于设备限制，试验期间可能无法满足这一要求。本文提出了一种简单可靠的方法，用于校正由非垂直性引起的误差。该方法基于图像特征匹配与校正，无需额外设备。论文进行了理论误差分析，以量化相机非垂直对准对测量精度的影响。所提出方法通过合成图像进行了数值验证，并在AC断裂试验中进行了实验验证。即使在相当大的相机旋转角度和大变形条件下，该方法也取得了较高精度。作为一种预处理技术，所提出方法在辅助近期开发的CrackPropNet进行非垂直相机对准条件下的自动化裂纹扩展测量方面表现出良好性能。
英文摘要：
Two-dimensional digital image correlation (2D-DIC) is a widely used optical technique to measure displacement and strain during asphalt concrete (AC) testing. An accurate 2-D DIC measurement can only be achieved when the camera's principal axis is perpendicular to the planar specimen surface. However, this requirement may not be met during testing due to device constraints. This paper proposes a simple and reliable method to correct errors induced by non-perpendicularity. The method is based on image feature matching and rectification. No additional equipment is needed. A theoretical error analysis was conducted to quantify the effect of a non-perpendicular camera alignment on measurement accuracy. The proposed method was validated numerically using synthetic images and experimentally in an AC fracture test. It achieved relatively high accuracy, even under considerable camera rotation angle and large deformation. As a pre-processing technique, the proposed method showed promising performance in assisting the recently developed CrackPropNet for automated crack propagation measurement under a non-perpendicular camera alignment.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
