Prediction of Forming Load for the Helical Gear Precision Forging by BP Neural Network

Abstract

Precision forging of the helical gear is a complex metal forming process under coupled effects with multi-factors. The high forming load is required to fill the teeth corner, which significantly causes failure, plastic deformation and wear of dies. The maximum forming load during precision forging helical gear is calculated by the finite element method (FEM). Combining the FEM simulation results with the artificial neural networks (ANN), backward propagation (BP) neural network is trained using the data of FEM simulation as learning sample. The trained BP neural network is validated using test samples and used to predict the maximum forming load under the different deformation conditions. The results show that the predicted results agree well with the simulated ones, the differences of prediction results exhibit low value, the predicted precision satisfy the request of industry.