摘要
机床的热误差建模与补偿技术是提高机床加工精度的行之有效方法,而关键温度测点的选择是成功实施该技术的重要前提,由此提出一种基于偏相关-灰色综合关联度的温度测点优化方法。采用偏相关分析法,分析单一温度测点与主轴热误差间的相关性,剔除掉不相关或弱相关的测点,对剩余测点进行基于灰色综合关联度算法的分析,量化各测点与机床主轴热误差间的紧密程度,将测点数量由16个减少至4个。根据优化结果,建立4测点的热误差预测模型,分析表明,主轴Z向最大热误差由10.338μm减小至1.299μm,验证了温度测点优化结果的有效性。
A newmethod is proposed to optimize the temperature measuring points of thermal error compensation technology for machine tools. A PC（ Partial Correlation） analysis method is used to weed out measuring points which are unrelated to spindle Z thermal error by controlling other variables. Then GSDA（ Grey Synthetic Degree of Association） is used to determine the correlation between the thermal error and measuring points. The key measuring points are achieved and the number is reduced from 16 to 4. Then a thermal error model is built based on these key temperature measuring points. The result shows that the Z-axis thermal error is reduced from 10. 338 μm to 1. 299 μm which validates the method＇s effectiveness.
作者
孟祥忠
MENG Xiang-zhong(Dalian Vocational Technical College,Dalian Liaoning 116035,China)
出处
《组合机床与自动化加工技术》
北大核心
2018年第8期127-130,共4页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国家自然科学基金(51675353)
