高速铣削SKD61模具钢表面完整性与疲劳寿命  

Surface integrity and fatigue life in high-speed milling of die steel SKD61

作　　者：王义强[1] 韩子渊[1,2] 叶国云 张占辉[1,2] 张志杰[1,2] 

机构地区：[1]浙江大学宁波理工学院,浙江宁波315100 [2]太原科技大学机械工程学院,山西太原030024 [3]宁波如意股份有限公司,浙江宁波315600

出　　处：《计算机集成制造系统》2015年第11期2995-3000,共6页Computer Integrated Manufacturing Systems

基　　金：国家科技重大专项资助项目(2012ZX04011021);浙江省自然科学基金资助项目(Y1110708)~~

摘　　要：为探究高速铣削加工中表面完整性对零件疲劳寿命的影响规律,使用圆环面铣刀对SKD61模具钢进行了高速铣削试验,并测定铣削后样件的表面完整性与疲劳寿命,根据表面完整性的量化指标,采用人工神经网络方法构建疲劳寿命预测模型。研究表明：铣削加工产生的表面残余压应力能显著延长零件的疲劳寿命。在一定范围内,零件的疲劳寿命分别随表面粗糙度和表面硬度的变化而剧烈变化。将表面完整性和人工神经网络相结合构建的零件疲劳寿命预测模型,其预测值与实测值的误差为2.3%~15.8%。To explore the effect of surface integrity on fatigue life,the high-speed milling experiment was conducted with die steel SKD61.The surface integrity and fatigue experiment were carried out on the test prototype.The prediction model of fatigue life was built according to the surface integrity quantitative indicators.The research showed that surface residual compressive stress could extend the fatigue life of parts significantly.In a certain extent,the fatigue life of parts would vary rapidly with the change of surface roughness and surface hardness.The fatigue life could be predicted by the prediction model according to the BP neural network,and the errors of predicted and tested data range were 2.3%to 15.8%.

关 键 词：机械制造工艺与设备 高速铣削 表面完整性 疲劳寿命 人工神经网络 

分 类 号：TH164[机械工程—机械制造及自动化] TG115.57[金属学及工艺—物理冶金]