斑点图案
数字图像相关
位移场
稳健性(进化)
材料科学
流离失所(心理学)
变形(气象学)
光学
计算机科学
人工智能
声学
结构工程
工程类
物理
有限元法
基因
复合材料
化学
生物化学
心理学
心理治疗师
作者
Shanshan Yu,Jian Zhang,Chengpeng Zhu,Zeyang Sun,Shuai Dong
标识
DOI:10.1016/j.ymssp.2024.111131
摘要
An enhanced full-field deformation and crack measurement method for oblique optical-axis conditions was proposed. First, the thickness of the calibration plate causes an error in the homography conversion (H matrix) and the final displacement results. To solve this problem, a Perspective-n-Point (PnP) based thickness compensation method for H calibration was proposed. Second, for better measurement of the full-field deformation, the measured surface is mapped with random speckles and markers, and the complex background and covering problems create obstacles for crack skeleton detection. To overcome these interferences, a strain-guided two-phase detection method based on the deep learning model was innovatively designed. Third, the traditional crack width calculation method is susceptible to the binarization threshold and the connection to the speckles, and a crack width calculation method using the displacement of control points was suggested. During a bending test, the above methods were applied to a basalt fiber-reinforced polymer (BFRP) beam. The enhancement in the displacement measurement accuracy and the robustness of crack detection, particularly the potential of detecting hidden cracks, were verified by comparing the performance of the proposed method to that of traditional contact sensors.
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