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二级螺旋齿轮减速机的自动优化设计外文翻译

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Abstract The design space of multi-stage transmissions is usually very large and heavily constrained. This places significant demands on the algorithm employed to search it, but successful optimization has the potential to yield considerably better designs than conventional heuristics, at the same time enabling a better understanding of the trade-offs between various objectives (such as service life and overall weight). Here we tackle a two-stage helical gear transmission design problem (complete with the sizing and selection of shafts, bearings, housing, etc.) using a two-phase evolutionary algorithm in a formulation that can be extended to include additional stages or different layouts.
Keywords Evolutionary optimization • Gear train design •Spur gear sets • Punctuated equilibria • Multi-objective optimization
摘要:多级传输的设计空间通常非常大,但被严重制约。这明显要求搜索它的算法,但成功的优化,有可能会产生比传统的启发式更大更好的设计,在同时使更多的权衡更好地了解之间(各种目标,如使用寿命和整体重量)。在这里,我们处理一个两级螺旋齿轮传动设计问题(与完整的选型对轴,轴承,箱体等)使用两阶段的进化算法在一个可以扩展到制定包括额外的阶段或不同的布局。
关键词:进化优化•齿轮列车设计单齿轮套•间断平衡•多目标优化
1 Introduction
The complexity of the design of multi-stage reducers lies in the strong and often intractable connections between the design variables defining its sub-systems. In other words, an optimal reducer is generally not an assembly of components optimized in isolation, a fact overlooked by many conventional design heuristics. For instance, the impact of a certain choice of gear width and center distance may yield a minimum mass gearing, but the selection of this gearing may cascade through subsequent steps of the design process (sizing of shafts, further stages, bearings, housing,
etc.) to ultimately lead to a heavier reducer than if a slight compromise had been made on the choice of that first gearing.
1简介
多级减速机设计的复杂性在是强大的,而且往往难以设计其变量之间的关系,并界定其子系统。换句话说,最佳减速器通常不是一个组装优化孤立的部件,忽略了一个很多即传统设计启发的事实。例如,一个影响齿轮宽度和中心距的选择可能会产生一定的最低大规模负载,但该传动装置的选择可通过级联的设计及随后的步骤进程(上箱槽,进一步阶段,轴承,箱体等),最终导致1比如果较重的减速器轻微的妥协已经作出关于第一齿轮的选择。

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