关键词: 航空发动机, 叶片, 残余应力, 径向基函数神经网络, 球头刀高温合金GH4169

Abstract: To obtain compressive residual stress in milling aviation engine blade,the Radial Basis Function (RBF) neural network was introduced to predict the residual stress for high-temperature alloy GH4169.The lateral inclination angle,cutting speed and feed were taken as design factors to develop the ball-end milling experiments,and X-ray method was used to test residual stress.The RBF neural network was trained by using the experimental samples,and the result showed that RBF neural network had the best performance on prediction accuracy compared with Back Propagation (BP) neural network and conventional multiple linear regression method.The interaction effect of process parameters on residual stress was researched,and the result revealed that there was strongly nonlinear relationship between residual stress and process parameters.The proposed RBF model of residuals stress could be used for further process optimization of milling aviation engine blade.

Key words: aviation engine, blade, residual stress, radial basis function neural network, ball-end mill high-temperature alloy GH4169