基于差异演化算法的滚齿工艺参数优化决策

o solve the low efficiency of optimization decision during gear hob machining process, this paper proposed optimization decision of gear hobbing process parameters method based on difference evolution algorithm. Gear hobbing process parameters populations were presented and coded firstly. Then population optimization learning strategies were confirmed. What's more, the fitness function about multi-source information was built, such as machining quality, machining time, source consummation. Finally, Self-adaptive adjustment was conducted based on DE. Compared with the method of high-speed cutting parameters optimization decision based on graph theory and fuzzy TOPSIS, it has higher efficiency and better integrated processing effect.