基于三坐标测量机双参数向自适应测量自由曲面

发布时间：2018-03-23 20:16

本文选题：自由曲面　切入点：三坐标测量机　出处：《中国机械工程》2017年05期

【摘要】：提出一种基于三坐标测量机的双参数向自适应测量自由曲面方法。CMM手动测量被测曲面边界点后,连接点生成可测区域,由可测区域自动拓扑生成几条均布初始扫描线以及每条扫描线的均匀初始点,对于U向的各条扫描线,CMM在自动测完初始点后,不断拟合已测点为B样条曲线,由曲线末端曲率自适应预测下一测点并指导CMM自动测量。测完初始扫描线后拟合已测点云为B样条曲面,由曲面V向边界最大曲率自适应确定下一扫描线位置,并进行该条扫描线U向自适应测量,重复这一过程直至曲面测量完毕。测点可随被测曲面自身曲率变化特性而疏密分布,曲率变化大的重要特征区域分布密集,曲率变化小的非重要区域分布稀疏,既保证了重要特征点不会遗漏又避免了数据冗余。理论曲线曲面自适应测量实验结果表明该方法测量精度可达微米级,实例零件应用验证了该方法的可行性。
[Abstract]:A two-parameter adaptive free-form surface measurement method based on CMM. CMM is proposed to measure the boundary points of measured surfaces manually. Several uniformly distributed initial scanning lines and the uniform initial points of each scan line are generated from the automatic topology of the measurable region. For each scanning line in U direction, the CMM continuously fits the measured points to B-spline curve after the initial point is automatically measured. The curve end curvature adaptively predicts the next measuring point and guides the CMM automatic measurement. After the initial scanning line is measured, the cloud of measured points is fitted as a B-spline surface, and the position of the next scan line is determined adaptively by the maximum curvature of the curved surface V direction boundary. The U direction adaptive measurement of the scanning line is carried out, and this process is repeated until the surface measurement is finished. The measured points can be distributed closely with the curvature characteristics of the measured surface, and the important feature areas with large curvature change are densely distributed. The sparse distribution of non-important regions with small curvature changes ensures that important feature points are not omitted and data redundancy is avoided. The experimental results of adaptive measurement of theoretical curves and surfaces show that the accuracy of this method can reach micron order. The feasibility of the method is verified by the application of practical parts.
【作者单位】：江苏省食品先进制造装备技术重点实验室;江南大学理学院;
【基金】：国家自然科学基金资助项目(51275210,51105175) 江苏省产学研项目(BY2013015-30) 江苏省六大人才高峰项目(2013-ZBZZ-016) 中央高校基本科研业务费专项资金资助项目(JUSRP51511)
【分类号】：TP391.7

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