基于复杂网络理论的发射平台抗毁伤网络拓扑性质研究

doi:10.12305/j.issn.1001-506X.2023.10.20

Abstract

Abstract:

A method for analyzing the anti-damage network of launch platforms based on damage flow infor-mation transmission is proposed to address the relative importance weighting of each subsystem in the evaluation of anti-damage capability of launch platforms. Taking a certain launch platform as the research object, this paper analyze the network topology properties by constructing its anti-damage network topology model. A mutual information model is proposed to calculate the weights of key components based on the functional operation characteristics of the launch platform, and a method for characterizing the anti-damage ability of the launch platform based on node connectivity is proposed. The research results indicate that the anti-damage analysis method based on complex network comprehensively considers the relationship of the overall layout and structural functional, making the evaluation results more systematic and comprehensive. The use of the mutual information model can objectively calculate the importance of key nodes in the network, reducing the impact of subjective weighting. The use of node connectivity can characterize the difficulty of transmitting damage flow information in the transmitting platform. The research results can provide reference for the evaluation and optimization of the anti-damage ability of launch platforms.

Key words: complex network, damage flow information, mutual information model, connectivity

CLC Number:

E917

Tong HUANG, Qinhe GAO, Zhihao LIU, Dong WANG, Dong MA, Lei GAO. Topological properties of launch platform anti-damage network based on complex network theory[J]. Systems Engineering and Electronics, 2023, 45(10): 3157-3164.

Figures/Tables 11

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参数	取值	参数	取值
节点数(n)	37	聚类系数(C)	0.166 7
边数(M)	109	平均最短路径(L)	0.277 7
平均度(<k>)	5.892	网络直径(D)	5

节点	代表部件	互信息值	归一化
2	发射筒	19.442 3	0.421 8
3	驾驶室	7.167 0	0.155 5
4	设备舱	2.530 2	0.054 9
5	轮胎	16.950 4	0.367 8

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Topological properties of launch platform anti-damage network based on complex network theory

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