基于MAGA一次包络TI蜗杆传动参数优化  

Parameter Optimization for Single-enveloping TI Worm Gearing Based on MAGA

作　　者：段路茜[1] 孙月海[2] 王树人[2] 张策[2] 

机构地区：[1]装甲兵工程学院,北京100072 [2]天津大学,天津300072

出　　处：《中国机械工程》2008年第5期531-534,共4页China Mechanical Engineering

基　　金：国家自然科学基金资助项目(50275103);装甲兵工程学院创新基金资助项目(2006ZL13)

摘　　要：以螺旋角、法向模数及蜗轮齿宽为优化变量,采用改进的自适应遗传算法(MAGA)对一次包络TI蜗杆传动进行多目标优化设计。为提高TI蜗杆承载能力、获得良好的蜗杆传动啮合性能,以接触线方向和相对速度方向的夹角、诱导法曲率为优化目标。优化结果表明:采用MAGA进行一次包络TI蜗杆传动参数优化是行之有效的。和传统优化方法相比,MAGA所得优化结果更加合理。Magnified Adaptive Genetic Algorithm （MAGA） was adopted to make a multiobjective optimum design for single-enveloping TI worm gearing. The helix angle, normal module and tooth width of worm gearing were selected as optimization variable. For better meshing performance, included angle between directions of relative velocity and contact line, and induced normal curvature were selected as optimization objects. The optimal results show that it is practicable and effective to apply MAGA to the parameter optimization for single-enveloping TI worm gearing. Compared with conventional optimum methods, the optimal result obtained from MAGA is more reasonable.

关 键 词：改进的自适应遗传算法(MAGA) TI蜗杆传动 参数优化 啮合性能 

分 类 号：TH132.41[机械工程—机械制造及自动化]