1. 西安交通大学陕西省智能机器人重点实验室
2. 西安交通大学机械制造系统工程国家重点实验室
纸质出版:2019
移动端阅览
朱星星, 赵亮, 雷默涵, 等. 精密进给系统热误差的协同训练支持向量机回归建模与补偿方法[J]. 西安交通大学学报, 2019,(10):40-47.
针对精密进给系统热误差的数据稀缺且获取成本高的问题
提出了一种基于协同训练支持向量机回归算法(COSVR)的精密进给系统热误差建模与补偿方法。通过整合标记数据(温度和热误差)及未标记温度数据建立热误差模型
利用基于西门子840D数控系统开发的补偿方法进行补偿。以精密镗床双驱动滚珠丝杠进给系统X轴为研究对象
进行热特性实验
获取24 m/min进给速度下的标记数据和12 m/min进给速度下的未标记温度数据
利用COSVR整合所有数据建立热误差模型
并通过遗传算法优化的支持向量机回归算法(GA-SVR)仅选用标记数据建立对照模型
获取18 m/min进给速度下的标记数据用于模型性能测试。结果表明:与GA-SVR模型相比
COSVR模型的均方根误差减少了34.14%
且在100 min和520 min时的误差范围分别减小了62.62%和55.85%。COSVR模型具有更好的预测性能且能更有效地降低热误差
进一步提高了精密进给系统热误差的建模精度。
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