圆环面铣刀高速铣削S50C模具钢的工艺参数研究  

Research on Process Parameters of Toroidal Cutter in High-speed Milling of Die Steel S50C

作　　者：王义强[1,2] 闫国琛[1,2] 袁修华[1] 谷岩[1] 杨林霖[1] 

机构地区：[1]浙江大学宁波理工学院,浙江宁波315100 [2]浙江省零件轧制成形技术研究重点实验室,浙江宁波315100

出　　处：《兵工学报》2014年第7期1091-1096,共6页Acta Armamentarii

基　　金：浙江省自然科学基金项目(Y1110708);国家科技重大专项(2012ZX04011021);宁波市自然科学基金项目(2013A610152)

摘　　要：为了探究高速铣削过程中工艺参数对表面粗糙度的影响规律,采用多因素正交试验方法对常用模具钢S50C进行高速铣削试验,测量了使用圆环面铣刀铣削加工时不同主轴转速、进给速度、切削深度、切削行距、刀具倾角下加工工件的表面粗糙度,利用人工神经网络结合遗传算法建立了表面粗糙度预测与工艺参数优选模型,并且对模型的有效性进行了验证。结果表明,此方法可以用于切削加工前表面粗糙度的预测与工艺参数的优选,同时也为其他材料加工工艺参数的研究提供了方法。In order to explore the effect of process parameters on surface roughness in high-speed milling, the muhifactorial orthogonal experiments of die steel $50C are conducted, and the surface roughness is measured under different parameters such as spindle speed, feed rate, axial depth, radial width and pose angle. The artificial neural network and genetic algorithm are used to establish a prediction model of sur- face roughness and an optimization model of process parameters. In addition, the validity of two models is verified. Results show that the approach may be used for the prediction of surface roughness and optimi- zation of the process parameters before machining. Moreover, this research also provides a valid means to study the process parameters of other materials.

关 键 词：机械制造工艺与设备 高速铣削 圆环面铣刀 工艺参数 人工神经网络 遗传算法 

分 类 号：TG543[金属学及工艺—金属切削加工及机床]