摘要
针对现有三坐标测量机检测路径规划方法的不足,提出和构建了零件检测特征群数学模型和求解流程,在此基础上,根据检测工作平面、检测测头及检测测针变动次数和检测路径构建优化目标函数,从宏观和微观两个层面分别应用矩阵交叉遗传算法和序列规划遗传算法进行零件检测特征路径的优化求解。最后以Hexagon公司检测零件为例,说明了零件初始检测信息的获取以及算法的优化求解过程。实践证明,该方法快速有效,且具有良好的工程应用价值。
In order to improve the defects in present methods of CMM inspection path planning,a part measuring feature group model and solution processes were proposed.Then according to the characteristics of the mathematical model,a fitness function module was constructed based on the changing times of working planes,inspection angles,checking probe and the distance of detection paths.From macro and micro angles,the matrix crossover GA and sequence planning optimization GA were applied for solving optimization of inspection path planning.Finally,taking testing part of Hexagon Company for an example,the part initial checking data was acquired as well as the optimization algorithm for solving process was described.Practice proved that this method is fast and effective with good engineering application values.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2016年第12期1626-1631,共6页
China Mechanical Engineering
基金
江苏省青蓝工程资助项目(2014)
南通市科技计划资助项目(CP22013002
BK2014027)
关键词
三坐标测量机
测量路径规划
遗传算法
矩阵交叉
序列规划
coordinate measuring machine（CMM）
inspection path planning
genetic algorithm（GA）
matrix-cross
sequence planning
