Wang Liangliang, Peng Jinshuan, Shao Yiming. Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy[J]. 2015,39(7):16-19.
Wang Liangliang, Peng Jinshuan, Shao Yiming. Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy[J]. 2015,39(7):16-19. DOI: 10.16578/j.issn.1004.2539.2015.07.004.
基于逆可靠性策略的齿轮减速器多学科协同可靠性分析
摘要
针对现有的多学科可靠性分析方法只进行系统级优化,使系统级优化器的工作负担过重、求解效率低下的问题,提出了一种基于逆可靠性策略(Inverse Reliability Strategy,IRS)的多学科遗传协同(Collaborative Optimization Based On Genetic Algorithm,GA-CO)可靠性分析方法(IRS-GA-CO)。该方法将IRS方法与多学科协同优化算法结合进行复杂系统工程可靠性分析。同时,采用遗传算法求解系统级可靠性优化问题,克服多学科协同优化算法中拉格朗日乘子不存在的缺陷。在IRS-GACO方法中所有的学科能够独立的进行优化,这样不仅解除了所有学科之间的耦合,提高了搜索最大可能点(Most Probable Point,MPP)的效率,而且学科级能进行优化,系统级优化器的负担可显著地降低。通过一个数学算例和齿轮减速器多学科可靠性分析的工程例子证明了文中提出方法的效率和精度,这个优点在大规模的复杂工程系统的设计中能够更好地体现出来。
Abstract
To overcome the high computational cost of reliability analysis,a reliability analysis method which combines the multidisciplinary genetic algorithm collaborative optimization( GA- CO) based on the inverse reliability strategy( IRS) is proposed( IRS- GA- CO). The genetic algorithms- based collaborative optimization( GA- CO) is one of the improved forms of CO that overcomes the difficulty of convergence given the existing of highly nonlinear consistency constraints. The IRS- GA- CO,which not only lifted the coupling between all disciplines to improve the search most probable point,the burden of system- level optimizer also can be significantly reduced. Examples of speed reducer prove the efficiency and precision of the proposed method.What is more,this advantage in the design of large- scale complex engineering systems will be better reflected.