摘要
使用PCBN刀具对不同淬硬状态工具钢Cr12MoV进行了精密干车削试验,利用正交回归法与响应曲面法,建立了以切削速度v、切削深度口a_p、走刀量f、工件淬火硬度H、刀尖半径r_ε为影响因素的已加工表面温度θ_W的指数与二次多项式预测模型。同时,运用方差法,分析了切削速度v、切削深度a_p、走刀量f、工件淬火硬度日、刀尖半径r_ε的主效应及二次交互效应对已加工表面温度θ_W影响的显著性。结果表明:ORM指数模型的绝对误差为8.5%,二次RSM多项式模型的绝对误差为2.3%,二次RSM多项式模型的预测值与试验值的吻合性比较好。
An experiment investigation of finish dry hard turning(FDHT) various hardened tool steel Crl2 MoV is conducted with the PCBN cutting tool.The exponential and quadratic polynomial predictive model for temperature on the machined workpiece surface by employing the factors,such as the cutting speed,depth of cut,feed,the hardness of the hardened steel and the nose radius,are developed by utilizing the orthogonal regression methodology(ORM) and response surface methodology(RSM).Meanwhile,the effects of the main factors which include the cutting speed,depth of cut,feed,the rake angle of the tool,the hardness of the hardened steel and the nose radius,and their interaction effects on the temperature of machined workpiece surface are investigated,based on the orthogonal experiment by using analysis of variance(ANOVA).The experimental results indicate that the absolute error of the ORM exponential predictive model is 8.5%,while that of the RSM quadratic polynomial predictive model is only 2.3%,which shows that the RSM quadratic polynomial predictive model best fits the variation of the temperature on the machined workpiece surface.
出处
《制造技术与机床》
北大核心
2014年第9期98-103,共6页
Manufacturing Technology & Machine Tool
基金
兰州工业学院青年科技创新计划项目(13K-001)
甘肃省高等学校科研项目(2013A-131)
