二阶螺旋齿轮减速器英文文献和中文翻译(7)

whether this is a problem-dependent number. Indeed, it is uncertain whether the feasibility percentage is a good indicator of the optimum switching moment. Similarly, further (broader) studies may reveal more effective ways of deciding on the best moment to switch back for a another constraint satisfaction phase.

References

Abersek B, Flasker J, Balic J (1996) Expert system for designing and manufacturing of a gear box. Expert Syst Appl 11(3):397–405

Cohoon JP, Hegde SU, Martin WN, Richards DS (1991) Distributed genetic algorithms for the floor plan design problem. IEEE Trans Comput-Aided Des 10(4):483–492

DIN (1987) 3990 Teil 3 Tragfähigkeitsberechnung von Stirnrädern. Deutsches Institut Für Normung EV

Eldredge N, Gould SJ (1972) Punctuated equlibria: an alternative to phyletic gradualism. In: Schopf T (ed) Models in paleontology. Freeman Cooper, San Francisco Ferguson GL, Robinson M Moynihan GP (1999) Expert system for

selecting speed reduction components for a power transmission. J Manuf Syst 18(1):66–74

Gologlu C, Zeyveli M (2009) A genetic approach to automate preliminary design of gear drives. Comput Ind Eng 57:1043–1051

Hamada M, Martz HF, Reese CS, Wilson AG (2001) Finding nearoptimal Bayesian experimental designs via genetic algorithms. Am Stat 55(3):175–181

Li R, Chang T, Wang J, Wei X (2008) Multi-objective optimization design of gear reducer based on adaptive genetic algorithm. In: 12th International Conference on Computer Supported Cooperative Work in Design

Lin Y, Shea K, Johnson A, Coultate J, Pears J (2009) A method and software tool for automated gearbox synthesis. In: Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 30 August–2 September, San Diego, California, USA, pp 1–11

Oh S, Yoon H (1998) An analysis of punctuated equilibria in simple genetic algorithms. Lect Notes Comput Sci 1363:195–206

Ray T, Liew KM(2003) Society and civilization: an optimization algorithm based on the simulation of social behavior. IEEE Trans Evol Comput 7(4):386–396

Ray T, Saini P (2001) Engineering design optimization using a swarm with an intelligent information sharing among inpiduals. Eng Optim 33(6):735–748

Talbi EG (2009) Metaheuristics: from design to implementation. Wiley, Hoboken

Thompson DF, Gupta S, Shukla A (2000) Tradeoff analysis in minimum volume design of multi-stage spur gear reduction units. Mech Mach Theory 35:609–627

摘要多级减速器设计空间通常有严重短缺。而这方面非常需求找到好的算法,但成功的优化方法比传统的启发式算法有更大的潜力,同时可以更好地理解权衡各种目标(如使用寿命和整体重量)。在这里我们解决一个二级螺旋齿轮传动设计问题(完整的尺寸和选择轴、轴承、减速器外壳等),利用两相演化算法这种方法法可以拓展出不一样的减速器包含额外的阶段或不同的布局。

关键词渐进结构优化••轮系设计•齿轮组 •间断平衡•多目标友化

介绍

多级减速器的设计的复杂性在于确定其子系统之间的设计变量困难而且连接棘手。换句话说，在优化的组件装配中一个最佳的减速一般是不隔离的，许多传统的设计启发式忽略了一个事实，例如，一个齿轮的宽度和中心距的必然选择的影响可能会产生一个最低的质量，整体负重，但这级联负重5月通过的设计过程中的后续步骤的选择（轴的大小，下一步阶段，轴承，外壳等），最终导致较大的减速比，如果已经有轻微的妥协，第一选择负荷。

一个典型的例子可能会选择比最优齿轮直径（和相应的更大的接触面宽度）较小，可能会产生一个有点沉重的负荷，但更紧凑的布局，因此，要轻得多的壳体，这是值得一提的影响，虽然这在现实中的总体目标，往往是直接和少得多，远远超过在这个例子中默默无闻。,源Z自L751:文,论/文]网[www.751com.cn。二阶螺旋齿轮减速器英文文献和中文翻译(7):http://www.751com.cn/fanyi/lunwen_51526.html