航空学报 > 2020, Vol. 41 Issue (5): 323632-323632   doi: 10.7527/S1000-6893.2019.23632

基于贝叶斯网络和共因失效的飞机电源系统可靠性分析

孔祥芬, 王杰, 张兆民   

  1. 中国民航大学 航空工程学院, 天津 300300
  • 收稿日期:2019-11-04 修回日期:2019-12-21 出版日期:2020-05-15 发布日期:2020-02-06
  • 通讯作者: 孔祥芬 E-mail:xfkong@cauc.edu.cn
  • 基金资助:
    国家自然科学基金(71902180);航空科学基金(20170267002);民航机场群智慧运营重点实验室基金(KLAGIO20180302)

Reliability analysis of aircraft power system based on Bayesian networks and common cause failures

KONG Xiangfen, WANG Jie, ZHANG Zhaomin   

  1. School of Aeronautical Engineering, Civil Aviation University of China, Tianjin 300300, China
  • Received:2019-11-04 Revised:2019-12-21 Online:2020-05-15 Published:2020-02-06
  • Supported by:
    National Natural Science Foundation of China(71902180); Aeronautical Science Foundation (20170267002);Civil Aviation Airport Group Smart Operation Key Laboratory Open Fund(KLAGIO20180302)

摘要: 飞机电源系统中的冗余设计提升了飞机系统的可靠性,但同时也增加了共因失效发生的概率。为了准确分析飞机电源系统的可靠性,首先,采取α因子模型对共因失效部件的失效率进行分解计算,并利用贝叶斯网络(BN)建立考虑共因失效的飞机电源系统可靠性模型。然后,对比分析考虑与不考虑冗余部件之间的共因失效因素时飞机电源系统及其子系统的可靠性。结果表明,考虑冗余部件之间的共因失效因素时,得到的飞机电源系统及其子系统可靠度相对于不考虑冗余部件之间的共因失效因素时较低,更加吻合实际情况。

关键词: 可靠性, 飞机电源系统, 共因失效, 贝叶斯网络, 冗余部件

Abstract: The redundant design in the aircraft power system increases both the reliability of the aircraft system and the probability of common cause failures. To accurately analyze the reliability of the aircraft power system, first, this study adopts the α factor model to decompose the failure rates of the common failure components, and the Bayesian Network (BN) to establish a reliability model of the power system considering the common cause failures. Then, comparative analysis of the reliability of the aircraft power system and its subsystems with and without consideration of common cause failures among redundant components is conducted. The results show a lower reliability of the obtained aircraft power system and its subsystems when the common cause failure factors among redundant components are considered than that without considering these factors, which is more consistent with the actual situation.

Key words: reliability, aircraft power system, common cause failure, Bayesian network, redundant components

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