基于钛合金的切削残余应力仿真及预测Simulation and Prediction of Cutting Residual Stress of Titanium Alloy
高秋阁,王团辉,辜茂
摘要(Abstract):
以Ti6Al4V为代表的钛合金因高强度、低密度和优良耐腐蚀性,在航空航天领域得到广泛应用,但加工过程中产生的残余应力会对零件寿命和性能产生不利影响。为研究其加工中的残余应力行为,采用二维建模模拟加工过程,用Johnson-Cook本构方程描述切削工况下材料力学行为,该方程综合考虑了应变、应变率、温度和材料特性对流动应力的影响。基于切削理论建立模型,仿真分析切削参数(切削速度、背吃刀量)对残余应力的影响,并用BP-神经网络算法综合分析预测。正交试验分析显示,切削速度对残余应力的影响强于背吃刀量,优化参数时应优先考虑调整切削速度。经训练的BP-神经网络模型对残余应力预测具备优异性能,决定系数最大值可达0.99,能有效表征切削参数与残余应力关系,可为钛合金切削加工的参数优化提供支持。
关键词(KeyWords): 残余应力;BP-神经网络;钛合金;CAE-abaqus
基金项目(Foundation):
作者(Author): 高秋阁,王团辉,辜茂
参考文献(References):
- [1]孟龙晖.Ti6Al4V钛合金切削加工表面残余应力的研究[D].南京:南京航空航天大学,2016.
- [2]Henriksen E K.Residual stresses in machined surfaces[C].ASME,1948.
- [3]Jang D Y,Watkins T R,Kozaczek K J,et al.Surface residual stresses in machined austenitic stainless steel[J].Wear,1996,194(1):168-173.
- [4]Tan L ,Zhang D ,Yao C ,et al.Evolution and empirical modeling of compressive residual stress profile after milling,polishing and shot peening for TC17 alloy[J].Journal of Manufacturing Processes,2017,26155-165.
- [5]Ee K ,Dillon O ,Jawahir I .Finite element modeling of residual stresses in machining induced by cutting using a tool with finite edge radius[J].International Journal of Mechanical Sciences,2005,47(10):1611-1628.
- [6]Durul U,Tugrul O.Machining induced surface integrity in titanium and nickel alloys:A review[J].International Journal of Machine Tools and Manufacture,2010,51(3):250-280.
- [7]孟龙晖,何宁,李亮,等.TC4零件铣削加工残余应力自平衡前值的测量及其有限元分析[J].稀有金属材料与工程,2014,43(08):1991-1996.
- [8]Yang J ,Xue Z ,Zhao T ,et al.Multi-source signals synthesized via CGAN as fused process signatures for space domain surface topography prediction[J].Mechanical Systems and Signal Processing,2025,233:112784.
- [9]张仲玺.复杂薄壁零件加工残余应力变形预测与控制方法[D].西安:西北工业大学,2021.
- [10]王卓.钛合金薄壁深腔框体铣削残余应力预测与工艺优化[D].上海:上海工程技术大学.
- [11]高秋阁,程东华.基于Ti6Al4V钛合金切削力的数值模拟及分析[J].机械管理开发,2025,40(06):1-4.
- [12]刘孟.基于改进混合多模型神经网络的切削力高精度预测研究[D].南宁:广西大学,2024.