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一种基于二次分配的测试性指标分配方法 被引量:4

A testability index allocation method based on quadratic allocation
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摘要 针对现有主流测试性分配方法均为一次性分配,缺乏必要的反馈和修正,一旦有单元分配指标过高无法实现,会导致系统指标也无法实现的问题,提出了一种基于二次分配的测试性指标分配方法。利用基于反正切函数的改进故障率分配法实施初次分配,由单元开展测试性初步设计和预计,基于单元测试性指标预计结果判断是否需要实施再次分配,如需要再次分配,则基于单元相对难度系数的修正函数,对指标偏高/偏低的单元实施再次分配,得到最终分配结果。通过仿真算例和实例验证了二次分配方法的有效性和先进性。 The existing mainstream testability allocation methods are all one-time allocation, without feedback and modification. Once the unit allocation index is too high to achieve, the system index cannot be achieved. Therefore, a testability allocation method based on quadratic allocation is proposed. First, an improved fault rate allocation method based on arctangent function is proposed to implement the primary allocation. Second, the preliminary design of testability and testability prediction are successively implemented to determine whether the secondary allocation is required. If it's required, an amending function based on the relative difficulty coefficient is proposed to implement the secondary allocation and obtain the final allocation result. Finally, the effectiveness and advancement of the quadratic allocation method are verified by simulation calculation and practical application.
作者 杨鹏 谢皓宇 邱静 YANG Peng;XIE Haoyu;QIU Jing(Science and Technology on Integrated Logistics Support Laboratory, School of Intelligence Science, National University of Defense Technology, Changsha 410073,China)
出处 《航空学报》 EI CAS CSCD 北大核心 2019年第9期293-301,共9页 Acta Aeronautica et Astronautica Sinica
基金 装备预研项目(41403020101)~~
关键词 测试性分配 二次分配 故障检测率 分配函数 相对难度系数 testability allocation quadratic allocation fault detection rate allocation function relative difficulty coefficient
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  • 1王跃宣,刘连臣,牟盛静,吴澄.处理带约束的多目标优化进化算法[J].清华大学学报(自然科学版),2005,45(1):103-106. 被引量:54
  • 2王宝龙,黄考利,苏林,魏忠林.基于遗传算法的复杂电子装备测试性优化分配[J].计算机测量与控制,2007,15(7):925-928. 被引量:8
  • 3崔逊学.多目标进化算法及其应用[M].北京:国防工业出版社,2008:4-12.
  • 4张永,吴晓蓓,徐志良,黄成,胡维礼.基于Pareto多目标遗传算法的模糊系统设计[J].南京理工大学学报,2007,31(4):430-434. 被引量:4
  • 5岳超源.决策理论与方法[M].北京:科学出版社,2004..
  • 6Srinivas N, Deb K. Multi-objective optimization using non-dominated sorting in genetic agorithms [J].Evolutionary Computation, 1994,2:221-248.
  • 7Deb K, Agrawl S, Pratap A, et al. A fast elitist non- dominated sorting genetic algorithm for multi-objective optimization:NSGA II [J]. Lecture Notes in ComputerScience ,2000,1917( 1 ) ,849-858.
  • 8Deb K, Pratap A, Meyarivan T. Constrained test problems for multi-objective evolutionary optimization [R]. KanGAL Report, Kanpur: Indian Institute of Technology, 2002.
  • 9国防科工委.GJB2547-95装备测试性大纲[S].北京:国防科学技术工业委员会,1995.
  • 10Elegbede C, Adiallah K. Availability Allocation to Repairable Systems with Genetic Algorithms: a Multi-objective Formu- lation [J]. Reliability Engineering and System Safety, 2003,82(8): 319-330.

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