西安交通大学机械工程学院,西安,710049
网络首发:2010-11-10,
纸质出版:2010
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唐正宗, 梁晋, 肖振中, 等. 大变形测量数字图像的种子点匹配方法[J]. 西安交通大学学报, 2010,44(11):51-55.
Digital Image Correlation Method Based on Seed Point for Large Deformation Measurement[J]. 2010, 44(11): 51-55.
针对数字图像相关方法中的大变形测量难题
提出了一种数字图像的种子点匹配方法.对于连续变形的图像系列
将图像子区划分后
选取其中任一子区作为种子点并进行相关匹配
根据相邻状态变形的连续性
提出了一种改进的整像素搜索方法
可保证种子点在大变形情况下仍能匹配成功.当种子点匹配完成后
根据同一状态相邻点变形的连续性
利用种子点的相关参数计算其4个邻近点的相关参数初值并完成匹配
按照同样的方法依次向外扩散
直至所有的点匹配完成.通过刚体旋转和单向拉伸实验表明
对于40°旋转图像的位移场以及高达113%的钢试件大变形
测量结果良好
具有较高的精度
证明了该方法的有效性.
To solve the problem of large deformation measurement with digital image correlation method
a method based on seed point is presented. Dividing subsets in the reference image
one point is chosen as the seed point and is matched first. Utilizing the deformation continuity of adjacent stages of a series images
an improved integer pixel search method is proposed
which guarantees that the seed point can be matched successfully even in large deformation situation. Once the seed point is matched
it can be used to calculate the initial correlation parameters of its four neighbor points following the deformation continuity of neighbor points in one stage
then the four neighbor points can be matched successfully. The above process repeats until all the points are matched. A rigid rotation experiment and a tensile test are carried out to verify the proposed method. The measurement results of 40 degrees rotation and large deformation up to 113% confirm the validity and precision.
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