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基于模糊C均值聚类法和多元线性回归理论的铣床热误差研究
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国家自然科学基金资助项目(51205067)


Research on Thermal Error of Milling Machine Based on Fuzzy C Mean Clustering Method and Multiple Linear Regression Theory
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    摘要:

    为了降低铣床主轴旋转受温度影响而产生的位移变形量,提高铣床对零件的加工精度,采用了模糊C均值聚类法和多元线性回归理论对铣床主轴的热误差进行建模,实现铣床主轴加工误差值最小化;分析了模糊C均值聚类法筛选最优值的迭代过程,对铣床上不同位置的测量温度值进行分组,筛选出每组的最优温度值;采用多元线性回归理论,对铣床热误差理论预测模型进行了推导,通过实验验证多元线性回归理论所创建的热误差预测模型。实验结果表明:补偿前,铣床主轴Y方向和Z方向受温度影响产生的热误差最大值分别为45.0 μm和28.0 μm;补偿后铣床主轴Y方向和Z方向受温度影响产生的热误差最大值分别为3.2 μm和3.8 μm,误差范围都在4 μm以内。采用模糊C均值聚类法和多元线性回归理论对铣床热误差进行补偿,铣床主轴运转受温度影响所产生的误差明显降低,从而提高了主轴定位精度。

    Abstract:

    In order to reduce the displacement deformation caused by the temperature effect on the spindle of the milling machine, to improve the machining accuracy of machine, the fuzzy C mean clustering method and multiple linear regression theory are used to model the thermal error of the spindle of the milling machine to realize minimized machining error of the spindle. The iterative process of selecting the optimal value of the fuzzy C mean clustering method was analyzed, the temperature value of different positions on the milling machine was divided into groups, and the optimal temperature value of each group was selected. By using the multiple linear regression theory, the thermal error theoretic prediction model of the milling machine was deduced, and the thermal error prediction model established by the multiple linear regression theory was verified by the experiment. The experimental results show that the temperature effect generated before the compensation, a milling spindle in Y and Z directions of thermal error maximum value respectively are 45.0 μm and 28.0 μm; after compensation, milling machine spindle in Y and Z directions by temperature thermal error maximum value respectively are 3.2 μm and 3.8 μm, and error bounds are less than 4 μm. Using fuzzy C means clustering method and multiple linear regression theory to compensate the thermal error of the milling machine, the error caused by the temperature influence on the main spindle of the milling machine is obviously reduced, thus improving the positioning accuracy of the spindle.

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余蔚荔,王素娟.基于模糊C均值聚类法和多元线性回归理论的铣床热误差研究[J].机床与液压,2018,46(1):32-35.
. Research on Thermal Error of Milling Machine Based on Fuzzy C Mean Clustering Method and Multiple Linear Regression Theory[J]. Machine Tool & Hydraulics,2018,46(1):32-35

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  • 在线发布日期: 2018-04-16
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