基于6σ稳健优化的减速器接触参数优化及误差控制研究

Research on Contact Parameter Optimization and Error Control of Reducer Based on Six Sigma Robust Optimization

为了降低锥齿轮啮合过程中安装误差,在安装误差前提下采取6σ稳健优化,采取MonteCarlo算法进行抽样,通过多岛遗传算法来优化二阶接触参数且对安装误差进行调整,比较分析确定性优化方法与本文所提优化方法的不同。研究结果表明:未优化参数安装误差印痕中心波动较大;利用确定性优化方法,提高了安装误差的稳定性,可靠度在99.9%以上,波动范围均没有超出优化边界,得到更强稳定性的齿轮系统。各二阶接触参数相应的印痕特点也有明显不同,使得各种安装误差下传动误差得到明显优化。与确定性优化方法相比,6σ优化方法可使传动误差波动降低30%,因此可知6σ稳健设计的可行性更强。文中设计的稳健性方法满足可靠性要求,可以拓宽到其它的机械传动领域。

In order to reduce the installation errors in the engagement process of bevel gears,six sigma robust optimization is adopted under the premise of installation errors.The MonteCarlo algorithm is adopted for sampling,and the multi-island genetic algorithm is used to optimize the second order contact parameters and adjust the installation errors.The differences between the deterministic optimization method and the proposed optimization method are compared and analyzed.The results show that the unoptimized parameter installation error center fluctuates significantly.Using the deterministic optimization method,the stability of the installation error is improved,the reliability is higher than 99.9%,and the fluctuation range does not exceed the optimization boundary,so the gear system with stronger stability is obtained.The corresponding printing characteristics of each second order contact parameter are considerably different,so that the transmission error can be optimized under various installation errors.Compared with the deterministic optimization method,the transmission error fluctuation can be reduced by 30%by the 6σoptimization method.Therefore,the feasibility of the 6σrobust design is superior.The robustness method designed in this paper meets the reliability requirements and can be extended to other fields of mechanical transmission.