中国机械工程2016，Vol.27Issue(20)：2705-2710,2711,7.DOI:10.3969/j.issn.1004-132X.2016.20.002
基于粒子群算法的滚削齿面综合轮廓误差预测模型与试验研究
A Prediction Model and Experimental Study of Gear Hobbing Profile Errors Based on Particle Swarm Optimization
摘要
Abstract
A series of 3 factors and 2 levels response surface method experiments were carried out to research the influence rules of processing parameters including the spindle speed,the feed rate in Z direction,and the hobbing depth on the gears’tooth profile errors on the precision horizontal gear hobbing machine equipped with home-made CNC system.The mathematical models of the total profile deviation,the total helix deviation and the total cumulative pitch deviation were built respectively and the influence degrees of the three gear profile errors were finished based on the statical experimental data analyses.A more appropriate model for gear profile errors was established based on the weighting factor of each deviation.A method of using particle swarm optimization to improve the gear hobbing parameters was applied based on the final mathematical model.The results show that it is feasible to preselect the hobbing parameters based on the particle swarm optimization of the gear profile errors model established by response surface method.关键词
粒子群优化算法/响应曲面法/滚齿加工/轮廓误差Key words
particle swarm optimization/response surface method/gear hobbing/profile error分类
机械制造引用本文复制引用
袁彬,韩江,吴路路,田晓青,夏链..基于粒子群算法的滚削齿面综合轮廓误差预测模型与试验研究[J].中国机械工程,2016,27(20):2705-2710,2711,7.基金项目
国家自然科学基金资助项目(51575154,51505118) （51575154,51505118）
