Abstract: Aiming at the problem that the gear affected the transmission efficiency of the reducer during the transmission process of the reducer, the factors affecting the gear transmission efficiency of the reducer were studied. A combination of the macro parameters of the gear and the optimization of the micro parameters was proposed to improve the transmission efficiency of the reducer. Firstly, the genetic algorithm was optimized for the macro parameters of the gears. Then the KRIGING algorithm was used to fit the relationship between the tooth shape modification parameters and the gear meshing power loss. The mean square error (MSE) criterion was used to improve the accuracy of the KRIGING prediction model. In the case of model accuracy requirements, the expected improvement (EI) criterion was used to find the optimal solution. Finally, the optimal parameters were input into the ROMAX software, and the optimal solution and simulation results were compared. The results indicate that the error of the optimal solution is only 0.179% compared with the simulation result, the gearbox transmission efficiency is increased by 0.5%.
Key words: genetic algorithm; gear shaping; KRIGING algorithm; mean square error (MSE) criterion; expected improveme