期刊文献+

面向飞行器发射控制系统可靠性提升的测试分析

Test and Analysis of Reliability Improvement in Aircraft Launch Control System
下载PDF
导出
摘要 系统的可靠性与测试性密切相关,良好的测试性设计,可以提升系统的可靠性,一个可靠的系统不是通过最后的测试结果测试出来的,而是在设计中将测试性考虑其中,系统测试性对系统的基本可靠性有着很大的影响;为了找到飞行器发射控制系统最优测试项,对可靠性与测试性二者的关联进行深入研究,通过系统设计初期的结构组成进行测试性分析,建立系统多信号流图模型,研究系统的相关性矩阵,并进行系统的故障检测率、故障隔离率等参数分析;提出了基于测试覆盖度的遗传算法进行测试项的优化选择,通过此方法进行实验仿真找到系统的最优测试项,成功满足系统的故障检测率、故障隔离率要求,将改进的遗传算法和传统的遗传算法进行对比,改进后的算法有着更好的收敛性,对系统分析更好。 The reliability of system is closely related to testability.A good testability design can improve the reliability of system.A reliable system is not tested by the final test results,but testability is considered in the design,which has a great influence on the basic reliability of the system.In order to find the optimal vehicle emission control system test,the association of the reliability and testability is deeply studied,through the system design of the early structure testability analysis,the system signal is established by the flow graph model,the system of the correlation matrix,and the system parameters such as fault detection rate and fault isolation rate analysis.The optimal selection of test items based on the test coverage of the genetic algorithm is proposed.This method is used to find out the optimal test item by the experimental simulation,the system fault detection rate and fault isolation rate requirement are successfully met,the improved genetic algorithm is compared with the traditional genetic algorithm,the improved algorithm has better convergence and analysis for the system.
作者 张子剑 姜利 龙中权 林海 刘虎 ZHANG Zijian;JIANG Li;LONG Zhongquan;LIN Hai;LIU Hu(Beijing Institute of Aerospace Systems Engineering,Beijing 100076,China)
出处 《计算机测量与控制》 2022年第10期63-69,共7页 Computer Measurement &Control
关键词 飞行器发射控制 系统可靠性 故障树分析 遗传算法 aircraft launch control system reliability fault tree analysis genetic algorithm
  • 相关文献

参考文献7

二级参考文献34

  • 1金星,洪延姬,张明亮,崔村燕,陈景鹏.大型复杂系统平均寿命评定的Monte Carlo方法[J].系统仿真学报,2005,17(1):66-68. 被引量:9
  • 2陈光禹.VIX总线测试平台技术[M].北京:电子科技大学出版社,1996.295-344.
  • 3于功敬.军用VXI测试系统的软件设计[J].计算机自动测量与控制,2000,(2):11-13.
  • 4玄光男 程润伟.遗传算法与工程优化[M].北京:清华大学出版社,2004..
  • 5De Bontridder KMJ,Halldorsson BV,Halldorsson MM,Hurkens CA J,Lenstra JK,Ravi R,Stougie L.Approximation algorithm for the test cover problems.Mathematical Programming-B,2003,98(1-3):477-491.
  • 6DasGupta B,Konwar K,Mandoiu I,Shvartsman A.Highly scalable algorithms for robust string barcoding.Int'l Journal of Bioinformatics Research and Applications,2005,1 (2):145-161.
  • 7Halldorsson BV.Algorithms for biological sequence problems[Ph.D.Thesis].Pittsburgh:Carnegie Mellon University,2001.
  • 8Young NE.Greedy algorithms by derandomizing unknown distributioms.Technical Report,T.R.1087,Ithaca:Cornell University,1994.
  • 9Borneman J,Chrobak M,Vedova GD,Figueora A,Jiang T.Probe selection algorithms with applications in the analysis of microbial communities.Bioinformatics,2001,17(Suppl.):S39-S48.
  • 10Berman P,DasGupta B,Sontag E.Randomized approximation algorithms for set mulficover problems with applications to reverse engineering of protein and gene networks.In:Proc.of the 7th Int'l Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX 2004).LNCS 3122,Berlin:Springer Verlag,2004.39-50.

共引文献55

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部