基于复杂网络的复杂产品系统关键节点辨识

doi:10.16731/j.cnki.1671-3133.2024.09.010

现代制造工程 ›› 2024, Vol. 528 ›› Issue (9): 65-72.doi: 10.16731/j.cnki.1671-3133.2024.09.010

基于复杂网络的复杂产品系统关键节点辨识

谷晓燕, 李俊, 陈梦彤

北京信息科技大学信息管理学院,北京 100192

收稿日期:2023-11-20 出版日期:2024-09-18 发布日期:2024-09-27
作者简介:谷晓燕,副教授,博士,主要研究方向为复杂网络、风险管理与智能决策等。E-mail:xiaoyangu@bistu.edu.cn; 李俊,硕士研究生,主要研究方向为复杂网络、风险管理等。E-mail:13323210353@163.com; 陈梦彤,硕士研究生,主要研究方向为大数据分析、复杂网络与风险管理等。E-mail:Chenmengtong0321@126.com

Key nodes identification of CoPS based on complex network

GU Xiaoyan, LI Jun, CHEN Mengtong

School of Information Management,Beijing Information Science & Technology University, Beijing 100192, China

Received:2023-11-20 Online:2024-09-18 Published:2024-09-27

摘要/Abstract

摘要： 复杂产品系统具有规模大、结构复杂等特点,从系统结构的视角辨识复杂产品系统关键节点,对于“事前”定位潜在风险源具有重要意义。针对目前“事后”追溯风险源难以保证复杂产品系统可靠运行及风险管理前瞻性等问题,考虑复杂产品系统的层级结构和子系统间风险的相互影响,提出了一种可用于“事前”风险管理的关键节点辨识方法。首先依据系统结构建立复杂网络;然后,构造零模型并结合网络统计特征初步划分节点集合,在此基础上引入线性阈值模型分析节点风险传播影响力,并基于风险的动态传播特征选取关键节点;最后,采用新舟700飞机的系统结构进行实证分析。结果表明,提出的方法有效地辨识了复杂产品系统的关键节点。

关键词: 复杂网络, 零模型, 线性阈值模型, 复杂产品系统, 关键节点

Abstract: Complex product systems are characterized by large scale and complex structure, the key nodes identification of complex product systems from the perspective of system structure is of great significance for locating potential risk sources in advance. In view of the current problems that it is difficult to ensure the reliable operation of complex product systems and forward-looking risk management by tracing risk sources ″afterwards″, a key node identification method for ″before the fact″ risk management is proposed considering the hierarchical structure of complex product systems and the interaction of risks among subsystems. First, a complex network is established based on the system structure. Secondly, the null model is constructed and combined with the network statistical characteristics to initially divide the set of nodes, based on which a linear threshold model is introduced to analyze the risk propagation influence of nodes, and key nodes are selected according to the dynamic risk propagation. Finally, the system structure of the Xinzhou 700 aircraft is used for empirical analysis. The result shows that the proposed method can effectively identify the key nodes of complex product systems.

Key words: complex network, null model, linear threshold model, Complex Product Systems(CoPS), key node

中图分类号:

谷晓燕, 李俊, 陈梦彤. 基于复杂网络的复杂产品系统关键节点辨识[J]. 现代制造工程, 2024, 528(9): 65-72.

GU Xiaoyan, LI Jun, CHEN Mengtong. Key nodes identification of CoPS based on complex network[J]. Modern Manufacturing Engineering, 2024, 528(9): 65-72.

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基于复杂网络的复杂产品系统关键节点辨识

Key nodes identification of CoPS based on complex network

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