摘要
采用有限元仿真技术,通过分析残余应力对压痕功与卸载斜率之间关系的影响,建立压痕的加载功、弹性恢复功、卸载斜率和材料的屈服强度、残余应力以及球压头半径之间的非线性关系。利用有限元仿真数据训练神经网络模型,建立压痕功、卸载斜率、屈服强度、硬化指数和残余应力之间的非线性映射关系来辨识残余应力。结果表明文中方法能有效获得残余应力值。
The effect of residual stress on the relationship between indentation work and unloading slope was analyzed. The non-linear relationship between loading work, elastic recovery work, unloading slope, yield strength of the material, residual stress and radius of the spherical indenter was established by using the finite element method. Based on finite element simulation data, neural network model was trained. A nonlinear mapping relationship between indentation work, initial unloading slope, yield stress, hardening index and residual stress was established to identify residual stress. The results show that the effective residual stress values can be obtained.
作者
金宏平
Jin Hongping(School of Mechanical Engineering,Hubei University of Automotive Technology,Shiyan 442002,China)
出处
《湖北汽车工业学院学报》
2019年第2期36-39,46,共5页
Journal of Hubei University Of Automotive Technology
基金
湖北省自然科学基金(2014CFB623)
湖北汽车工业学院博士基金(BK201303)
关键词
残余应力
球压痕
神经网络
residual stress
spherical indentation
neural network