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TC4钛合金铣削温度预测的试验及响应面法研究
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徐州市科技计划项目(KC20188);江苏省大学生实践创新训练计划项目(201810320024Z);江苏省研究生科研创新计划项目(KYCX20_2331)


Experiment and Response Surface Methodology Study on Milling Temperature Prediction of TC4 Titanium Alloy
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    摘要:

    为研究不同铣削参数下TC4钛合金铣削区域最高温度的变化,搭建TC4钛合金的铣削温度测试系统。使用红外热像仪实时采集刀具与工件接触区域的铣削温度,得到不同铣削参数下测温区域铣削温度的时间历程曲线;分析不同铣削参数下最高温度的变化特征。基于试验数据,在Design-Expert软件中进行以铣削参数为影响因素、以最高温度为响应值的响应面优化法试验,建立最高温度关于铣削参数的三元二次多项式回归模型。结果表明:随着铣削参数的增大,最高铣削温度总体呈上升趋势;所建立的铣削温度特征值回归模型是显著的,可以较好地预测最高铣削温度;通过对最高温度进行数值优化,可得到铣削温度特征值最低时的最佳铣削参数。

    Abstract:

    In order to study the change of the highest temperature in the milling area of TC4 titanium alloy with different milling parameters,a milling temperature testing system for TC4 titanium alloy was constructed.The infrared camera was used to collect the milling temperature of the contact area between the tool and the workpiece in real time,the time history curves of the milling temperature of the contact area with different milling parameters were obtained;the variation characteristics of the maximum temperature with different milling parameters were analyzed.Based on the test data,the response surface methodology with milling parameters as the influencing factors and the maximum temperature as the response value was carried out in the Design-Expert software,and the ternary quadratic polynomial regression model of the maximum temperature with respect to milling parameters was established.The results show that with the increase of milling parameters,the maximum milling temperature shows generally upward trend;the established eigenvalue regression model of milling temperature is significant and can be used to predict the maximum milling temperature well;through numerical optimization of the maximum temperature,the optimal milling parameters with the lowest milling temperature eigenvalue can be obtained.

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邓星,邵明辉,李顺才,胡雨婷. TC4钛合金铣削温度预测的试验及响应面法研究[J].机床与液压,2022,50(10):51-56.
DENG Xing, SHAO Minghui, LI Shuncai, HU Yuting. Experiment and Response Surface Methodology Study on Milling Temperature Prediction of TC4 Titanium Alloy[J]. Machine Tool & Hydraulics,2022,50(10):51-56

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  • 在线发布日期: 2022-06-30
  • 出版日期: 2022-05-28