Optimization design of gear with lead modification considering the effect of twist error

Twist error exists when continuously generating grinding helical gears with lead modification, which leads to problems such as meshing impact and low load bearing. To improve the meshing performance of helical gears with twist error, a multi-objective optimization design method is proposed. Firstly, the mathematical equation of helical gear tooth surface with twist error is established. With helix angle and the modified amount as design variables, the maximum contact stress and amplitude of loaded transmission error as objective functions, the loaded tooth contact analysis (LTCA) was carried out by finite element method (FEM) and 25 sets of data were obtained. Then the function model was constructed by the BP neural network, and a fast elitist nondominated sorting genetic algorithm (NSGA-II) is used to solve the model. The results show that the maximum contact stress and amplitude of loaded transmission error after optimization are reduced by 29.6 % and 92.2 % respectively.