基于聚类的关节式坐标测量机姿态优化方法  

Measuring posture optimization for articulated arm coordinate measuring machine based on cluster

作　　者：汪金鹏[1] 郭阳宽[1] 祝连庆[1] 潘志康[1] 

机构地区：[1]北京信息科技大学光电测试技术北京市重点实验室,北京100101

出　　处：《现代制造工程》2017年第3期141-144,共4页Modern Manufacturing Engineering

基　　金：国家自然科学基金资助项目(51075038;51375057);国家重大科学仪器设备研发专项项目(2013YQ22089304);长江学者和创新团队发展计划资助项目(IRT1212);北京市教委面上项目(KM201411232004)

摘　　要：为了提高关节式坐标测量机的精度,提出了一种基于聚类的测量姿态优化方法。在数学模型的基础上,通过对测量机的测量姿态信息进行聚类来形成簇,并对簇进行打分和提取,最后根据提取结果对测量姿态进行优化。实验结果表明,测量机精度受姿态影响较大,优化后精度提高了约1倍,为进一步研究奠定了基础。In order to improve the accuracy of articulated arm coordinate measuring machine, the measuring posture optimization based on clustering analysis was proposed. On the basis of the mathematical model, by using systematic cluster analysis, cluster of posture information was constructed, c/usters were extracted by scoring method. Measuring posture optimization was finished by re- sult of extraction. The experimental results show that the accuracy of the machine was greatly influenced by the measuring pos- ture, the measuring accuracy was improved by 1 time after the measuring posture optimization. It provides a basis for further re- search.

关 键 词：坐标测量机 聚类分析 姿态优化 数学模型 

分 类 号：TH721[机械工程—仪器科学与技术]