基于FDN的装备体系任务能力依赖性分析

doi:10.12305/j.issn.1001-506X.2021.06.33

系统工程与电子技术 ›› 2021, Vol. 43 ›› Issue (6): 1721-1728.doi: 10.12305/j.issn.1001-506X.2021.06.33

• 可靠性 • 上一篇

基于FDN的装备体系任务能力依赖性分析

陈宇奇^1,*, 徐廷学¹, 郝建平², 逯程³, 李志强⁴

1. 海军航空大学岸防兵学院, 山东烟台 264001
2. 陆军工程大学石家庄校区, 河北石家庄 050003
3. 海军装备部装备保障大队, 北京 100089
4. 中国人民解放军91388部队, 广东湛江 524024

收稿日期:2020-04-05 出版日期:2021-05-21 发布日期:2021-05-28
通讯作者: 陈宇奇
作者简介:陈宇奇(1992—), 男, 博士研究生, 主要研究方向为复杂系统可靠性分析与评估|徐廷学(1962—), 男, 教授, 博士, 主要研究方向为装备综合保障理论与运用|郝建平(1969—), 男, 教授, 博士, 主要研究方向为维修工程|逯程(1990—), 男, 工程师, 博士, 主要研究方向为可靠性建模与维修决策优化|李志强(1988—), 男, 工程师, 博士, 主要研究方向为可靠性建模与维修决策优化、复杂系统试验鉴定与定型
基金资助:
国家自然科学基金(51605487)

Task capability dependency analysis of weapon system of systems based on FDN

Yuqi CHEN^1,*, Tingxue XU¹, Jianping HAO², Cheng LU³, Zhiqiang LI⁴

1. Coast Guard Academy, Navy Aeronautical University, Yantai 264001, China
2. Shijiazhuang Campus, Army Engineering University, Shijiazhuang 050003, China
3. Equipment Support Brigade of Navy Equipment Department, Beijing 100089, China
4. Unit 91388 of the PLA, Zhanjiang 524024, China

Received:2020-04-05 Online:2021-05-21 Published:2021-05-28
Contact: Yuqi CHEN

摘要/Abstract

摘要：

为了深入分析装备体系内各装备系统在任务执行过程中自身性能退化对其相互依赖性的影响, 并准确把握体系内各装备系统在自身性能退化和相互依赖性的双重影响下其当前效能的演变规律, 对传统功能依赖网络分析(functional dependency network analysis, FDNA)方法进行了一定改进。引入自身效能退化系数, 给出考虑时间因素的动态FDNA算法; 以Markov过程为基础, 构建体系内装备系统的性能退化模型, 为自身效能退化系数的计算提供相应依据, 从而提出一种基于功能依赖网络的装备体系任务能力依赖性分析方法, 并用案例验证了方法的可行性。

关键词: 装备体系, 性能退化, 功能依赖网络分析, Markov过程, 依赖性分析

Abstract:

In order to deeply analyze the influence of the performance degradation of each equipment system in system of systems on interdependency among them and accurately grasp the evolution law of the current efficiency of each equipment system under the dual influence of its own performance degradation and interdependence. The traditional functional dependency network analysis (FDNA) method is improved and the self-effectiveness degradation coefficient is introduced to give a dynamic FDNA algorithm considering time factor. And the performance degradation model of the equipment system in system of systems is constructed based on the Markov process to provide the corresponding basis for the calculation of self-effectiveness degradation coefficient. Then, a task capability dependency analysis method of weapon system of systems based on the functional dependency network is proposed, and the feasibility of the method is verified by a case.

Key words: weapon system of system, performance degradation, functional dependency network analysis (FDNA), Markov process, dependency analysis

中图分类号:

TB114

陈宇奇, 徐廷学, 郝建平, 逯程, 李志强. 基于FDN的装备体系任务能力依赖性分析[J]. 系统工程与电子技术, 2021, 43(6): 1721-1728.

Yuqi CHEN, Tingxue XU, Jianping HAO, Cheng LU, Zhiqiang LI. Task capability dependency analysis of weapon system of systems based on FDN[J]. Systems Engineering and Electronics, 2021, 43(6): 1721-1728.

图/表 10

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参数设置	Garvey法	本文方法
参数设置	$ \begin{array}{*{20}{c}}{{{{\mathop{\rm SOD}\nolimits} }_{{O_{ij}}}} = {\alpha _{ij}}{O_i} + }{100\left( {1 - {\alpha _{ij}}} \right)}\end{array}$	$\left\{ {\begin{array}{*{20}{l}}{{{{\mathop{\rm SOD}\nolimits} }_{{O_{ij}}}} = \left[ {{\alpha _{ij}}{O_i} + 100 \times } \right.}\\{\left. {\left( {1 - {\alpha _{ij}}} \right)} \right]{\delta _j}}\\{{\delta _j} = \frac{{{\rm{S}}{{\rm{E}}_j}}}{{{\rm{BO}}{{\rm{L}}_{{O_j}}}}} \times 100\% }\end{array}} \right. $
O_i=100, SE_j=10	O_j=100	O_j=100
O_i=100, SE_j=5	O_j=100	O_j=50
O_i=100, SE_j=0	O_j=100	O_j=0
O_i=50, SE_j=10	O_j=55	O_j=55
O_i=0, SE_j=10	O_j=10	O_j=10
O_i=50, SE_j=5	O_j=55	O_j=27.5

节点编号	状态编号	对应效能值	瞬时状态转移强度(×10^-6/h)
节点编号	状态编号	对应效能值	λ₁₀	λ₁₂	λ₁₃	λ₀₂	λ₀₃	λ₂₃
N₁	1	100	15.2	13.2	14.5	16.5	20.5	16.8
	0	75	15.2	13.2	14.5	16.5	20.5	16.8
	2	50	15.2	13.2	14.5	16.5	20.5	16.8
	3	0	15.2	13.2	14.5	16.5	20.5	16.8
N₂	1	100	—	19.6	14.3	—	—	20.2
	2	50	—	19.6	14.3	—	—	20.2
	3	0	—	19.6	14.3	—	—	20.2
N₃	1	15	—	18	—	—	—	—
N₃	2	0	—	18	—	—	—	—
N₄	1	20	—	14.6	10.8	—	—	15.4
	2	10	—	14.6	10.8	—	—	15.4
	3	0	—	14.6	10.8	—	—	15.4

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基于FDN的装备体系任务能力依赖性分析

Task capability dependency analysis of weapon system of systems based on FDN

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