Rolling force prediction and analysis of three-roll planetary rolling process based on FEM

To predict the rolling force of three-roll planetary rolling process,3D thermo-mechanical coupled finite element model was built up.Uniform design method was used to arrange training samples of finite element simulations,and the simulation results were trained in BP neural network based on LM algorithm.The mapping relationship between process parameters and rolling force was established to predict rolling force at real-time.The effects of friction coefficient,offset angle and rotational speed of rollers on rolling force were analyzed using the trained neural network.The predicted results show that the effects of friction coefficient and offset angle on rolling force are multiple,and larger friction coefficient is useful to reduce rolling force when the rotational speed of the rollers is high.