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摘要: 针对柔性复合薄膜成形试验中极限应变难以测量的问题，提出一种基于双目立体视觉结合数字图像相关法的测量方法。首先对于薄膜材料成形过程中产生大变形或裂纹时图像难以匹配的问题，根据系列图像相邻状态变形的连续性，提出了一种图像匹配基准自适应更新的弱相关分步匹配方法；然后根据薄膜材料表面应变分布不同于钢制件的特性，提出了一种构建应变场截线来拟合薄膜材料的极限应变曲线的方法。专门组建视觉测定的软、硬件系统，通过Q235钢试件进行极限应变曲线测量并与坐标网格方法进行对比，材料极限应变精度能够提高0.02%，证明了本文方法的可行性和精确性。用7组PET/Nylon/Al foil/PP材料制备成的柔性复合薄膜试件进行实测，此方法及系统成功地完成了柔性复合薄膜材料的成形极限曲线测定。对比实验和实际测试证明，本文方法能够快速、准确地测量柔性复合薄膜材料在整个成形过程中的表面应变分布，与传统的坐标网格方法相比具有明显的优势，为测定薄膜材料的成形极限应变曲线提供了一种高可靠性、高精度的手段。Abstract: To address the difficulty in measuring the strain limit of pliable composite film forming tests, a measurement method based on binocular stereo vision combined with digital image correlation is proposed. Firstly, to address the image matching problem in large deformations or cracks in thin films, a weak-correlation step-by-step matching method based on adaptive updating of image matching benchmarks is proposed according to the continuity of adjacent state deformation of series images. Then, according to the differences in the surface strain distribution of the film material with that of the steel parts, a strain field is proposed to fit the limit strain curve of the film material. The software and hardware system of visual measurement is built, and the limit strain curve of a Q235 steel specimen is measured and compared to results from the coordinate grid method. The limit strain accuracy can be improved by 0.02%, which proves the feasibility and accuracy of this method. The pliable composite film specimens prepared by PET, Nylon, Al foil, PP were each measured. The method and system successfully completed the measurement of the forming limit curve of the pliable composite film. The comparative experiments show that the proposed method can quickly and accurately measure the surface strain distribution of pliable composite film during forming. Compared with the coordinate grid method, it has obvious advantages and provides a highly reliable and highly precise method for solving the forming limit strain curve of film materials.
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表 1 极限应变对
$ ({\varepsilon }_{1},{\varepsilon }_{2}) $ Table 1. Limit strain pair
$ ({\varepsilon }_{1},{\varepsilon }_{2}) $ 型号 第1组 第2组 第3组 第4组 第5组 第6组 第7组 网格方法 (0.46,−0.17) (0.45,−0.14) (0.42,−0.04) (0.39,0.01) (0.43,0.10) (0.46,0.17) (0.51,0.30) 本文方法 (0.44,−0.15) (0.43,−0.13) (0.40,−0.03) (0.37,0.03) (0.42,0.11) (0.46,0.19) (0.50,0.29) 
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表 2 相机标定内参数
Table 2. Camera calibration internal parameters
内参数 左相机 右相机 f/pixel 26.586 26.633 x0/pixel 1.042 6.006 y0/pixel 5.867 14.286 K1 −1.37×10−9 −1.623×10−9 K2 −3.291×10−17 1.003×10−16 K3 8.614×10−23 5.813×10−23 B1 −2.302×10−8 −1.703×10−7 B2 −2.052×10−8 −7.343×10−8 E1 −0.0002241 −0.0003031 E2 0.000443 0.0003076
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