计算机与现代化

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无失效数据机载多余度EWIS可靠性研究

  

  1. (1.海军航空大学作战勤务学院,山东烟台264001;2.海军航空大学岸防兵学院,山东烟台264001;
    3.91663部队,辽宁沈阳110000)
  • 收稿日期:2018-09-27 出版日期:2019-04-26 发布日期:2019-04-30
  • 作者简介: 肖楚琬(1985-),男,湖南益阳人,工程师,博士研究生,研究方向:适航性,装备综合保障; 通信作者:邓力(1985-),男,江西萍乡人,讲师,博士,研究方向:装备安全性,系统建模与仿真,E-mail: 377091490@qq.com。
  • 基金资助:
     国家自然科学基金资助项目(51505493)

Research on Zero-failure Data Airborne Redundancy EWIS Reliability

  1. (1. Combat Duty Academy, Naval Aeronautical University, Yantai 264001, China;
    2. Coast Defense Academy, Naval Aeronautical University, Yantai 264001, China;
    3. The 93033th Unit of PLA, Shenyang 110000, China) 
  • Received:2018-09-27 Online:2019-04-26 Published:2019-04-30

摘要: 针对高可靠度机载多余度EWIS各组成部分寿命服从指数分布但参数未知的情况,提出采用无失效数据可靠度分析方法评估EWIS的可靠度水平。通过Monte-Carlo仿真方法对连接形式为“先并联、后串联”EWIS各组成部分寿命进行抽样,利用“最小最大值”方法获得系统寿命的抽样值,用概率纸检验法初步判断EWIS寿命是否服从威布尔分布,再用Pearson拟合优度检验法判断EWIS寿命是否服从威布尔分布。结合无故障飞行时间的样本值与EWIS寿命服从威布尔分布的假设,采用无失效数据分析方法评估EWIS的可靠度水平。研究方法对机载多余度EWIS无失效数据可靠度分析有一定的贡献。

关键词: 电气线路互联系统(EWIS), 多余度设计, Monte-Carlo仿真, 无失效数据, 可靠性, 寿命分布函数

Abstract: Considering the life span of high reliability redundancy EWIS components obeying exponential distribution with unknown parameters, a zero-failure data reliability analysis method was put forward to evaluating the reliability of EWIS. Monte-Carlo sampling method was applied to parallel-series EWIS life span, and the “minimization maximum” method was used to get the EWIS life span. Probability paper test was used to judge whether EWIS life obey Weibull distribution initially, and then Pearson fitness test was used to identify the distribution obeying Weibull distribution or not. Taken zero-failure data flight samples and the hypothesis of EWIS life obeying Weibull distribution into account, the zero-failure data reliability analysis method was applied to evaluate the reliability of EWIS. The research method is meaningful for analyzing redundancy designed EWIS reliability with zero-failure data.

Key words: electrical wiring interconnection system, redundancy design, Monte-Carlo simulation, zero-failure data, reliability, life span distribution

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