基于CMM的叶片测点采样分布方法研究  

Research on CMM-based measuring points' sampling and distribution method of blades

作　　者：张现东[1] 卜昆[1] 程云勇[1] 董一巍[1] 

机构地区：[1]西北工业大学现代设计与集成制造技术教育部重点实验室,陕西西安710072

出　　处：《锻压技术》2012年第4期131-135,共5页Forging & Stamping Technology

摘　　要：三坐标测量是复杂叶片外形精度检测的重要手段之一。针对自适应曲率采样、混合采样在大曲率处采样点过密集及在小曲率处过稀疏的缺点,通过优化曲率半径比,并结合叶片的结构特征,提出了一种自适应的分段曲率采样算法,进而对叶片CMM测量点的采样分布进行研究。研究结果表明:在测量点数相同的情况下,与均匀采样和混合采样算法相比,分段曲率采样算法可以使测量点的分布能更好的反映叶片CAD形状,从而提高叶片的三坐标测量效率。Three-coordinate measuring is one of the most important methods for measuring complex blades. For the mix sampling, the measuring points are too dense in the large curvature area and too sparse in the small curvature area as compared with the adaptive curvature sampling. For this defect, on the basis of the optimization of curvature radius ratio, combining with the structure characteristics of blades, an adaptive sub-curvature sampling algorithm was pro- posed and established. Compared with uniform sampling and mixed sampling under the same number of measuring points, the distribution of measuring points better reflects the form of CAD by sub-curvature sampling algorithm. So this algorithm can improve the efficiency of measuring complex blades using CMM.

关 键 词：叶片 三坐标测量 分段曲率采样 均匀采样 混合采样 

分 类 号：TH721[机械工程—仪器科学与技术] TP391.72[机械工程—精密仪器及机械]