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针对提取航空发动机叶片截面特征参数的实用性要求,研究了基于无序点云数据的叶片截面特征参数提取方法.综合距离法和二分法的优点,采用基于矩形腐蚀法的距离-二分法对点云数据排序,基于最小包容区域直线和最小二乘圆拟合,提出了将整条叶片截面点云数据分割成前缘、后缘、叶盆和叶背4部分的自动分区方法,对特征参数提取方法做了研究并用VC++进行算法实现,使用UG/OpenGrip生成UG中叶片截面上的点云数据进行实验运算,计算精度达到10-4 mm,表明在实际测量和参数提取中算法误差可以忽略.
In order to extract practical parameters of blade cross-section parameters of aeroengine, a method of extracting characteristic parameters of blade cross-sections based on out-of-order point cloud data was studied. By using the advantages of distance and dichotomy, Based on the minimum inclusion region line and the least-squares circle fitting, an automatic partitioning method was proposed to segment the entire leaf section cloud data into four parts: leading edge, trailing edge, leaf pot and leaf back. The extraction method is studied and the algorithm is implemented by VC ++. The point cloud data in the blade cross section of UG is generated by UG / OpenGrip and the calculation accuracy reaches 10-4 mm, which indicates that the algorithm error can be neglected in the actual measurement and parameter extraction.