吉林大学学报(理学版) ›› 2023, Vol. 61 ›› Issue (6): 1387-1394.

• • 上一篇    下一篇

发动机系统电磁脉冲易损性评估的灰色Bayes网络模型

李传鑫, 赵昱, 孙铁刚, 孙晓颖   

  1. 吉林大学 通信工程学院, 长春 130012
  • 收稿日期:2022-11-22 出版日期:2023-11-26 发布日期:2023-11-26
  • 通讯作者: 赵昱 E-mail:yzhao@jlu.edu.cn

Grey Bayesian Network Model for Electromagnetic Pulse Vulnerability Assessment of Engine Systems

LI Chuanxin, ZHAO Yu, SUN Tiegang, SUN Xiaoying   

  1. College of Communication and Engineering, Jilin University, Changchun 130012, China
  • Received:2022-11-22 Online:2023-11-26 Published:2023-11-26

摘要: 首先, 针对实验数据有限、 信息不完全背景下导致的发动机系统电磁脉冲易损性评估不确定性问题, 通过引入灰色系统理论中区间灰数表征发动机系统部件敏感度阈值和故障逻辑关系的不确定性, 提出一种灰色Bayes网络模型, 以提升Bayes网络对不确定信息的处理能力. 其次, 以宽带高功率微波为例, 计算发动机系统区间灰数失效概率和传感器区间灰数后验失效概率, 其中前者表示发动机系统整体在强电磁脉冲作用下的生存能力, 后者反应了发动机系统失效条件下各传感器的易损顺序, 评估结论可为车辆电磁防护设计提供参考.

关键词: 发动机系统, Bayes网络, 灰色系统理论, 电磁脉冲易损性

Abstract: Firstly, aiming at the uncertainty problem of electromagnetic pulse vulnerability assessment of engine system under the background of limited test data and incomplete information,  we proposed  a grey Bayesian network model  to improve the processing ability of Bayesian network for  uncertain information by introducing the interval grey number in grey system theory  to characterize the uncertainty of components sensitivity threshold and fault logic relationship of engine system. Secondly, taking wideband high power microwave as an example, the interval gray number failure probability of engine system and the interval gray
 number posterior failure probability of sensor were calculated. The former represented the survivability of the whole engine system under the action of strong electromagnetic pulse, and the latter reflected the vulnerable sequence of each sensor under the failure condition of the engine system. The evaluation conclusions could  provide reference for electromagnetic protection design of vehicles.

Key words: engine system, Bayesian network, grey system theory, electromagnetic pulse vulnerability

中图分类号: 

  • TP391