东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2006, Vol. 27 ›› Issue (2): 213-216.DOI: -

• 论著 • 上一篇    下一篇

冗余系统共因失效概率预测模型

李翠玲;李剑锋;谢里阳;   

  1. 东北大学机械工程与自动化学院;沈阳理工大学;东北大学机械工程与自动化学院 辽宁沈阳110004;辽宁沈阳110168;辽宁沈阳110004
  • 收稿日期:2013-06-23 修回日期:2013-06-23 出版日期:2006-02-15 发布日期:2013-06-23
  • 通讯作者: Li, C.-L.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(50275025)

Model to predict probability of common cause failure in redundant system

Li, Cui-Ling (1); Li, Jian-Feng (2); Xie, Li-Yang (1)   

  1. (1) School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110004, China; (2) Shenyang Ligong University, Shenyang 110168, China
  • Received:2013-06-23 Revised:2013-06-23 Online:2006-02-15 Published:2013-06-23
  • Contact: Li, C.-L.
  • About author:-
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摘要： 根据可靠性数学理论,从零件失效物理模型应力-强度干涉模型出发,把零件失效概率看作是服从某种分布的随机变量,推导了冗余系统共因失效概率预测模型的数学表达式.通过Monte Carlo仿真法和神经网络技术,得到了该随机变量的分布类型及分布参数.该模型可以根据系统的有限失效数据预测系统任意阶失效概率,能够弥补传统共因失效模型的信息遗漏问题.最后给出实例,并与传统的BFR模型对比,结果表明,该方法比BFR模型更能精确地与实际吻合.

关键词: 共因失效, 应力-强度干涉模型, 零件失效概率, MonteCarlo法仿真, 神经网络

Abstract: According to the mathematical theory of reliability and the physical model of component failure, i.e. the stress-strength interference model, component failure probability is regarded as a random variable complying with a certain distribution. The mathematical expression of a prediction model of the probability of common cause failure in redundant system is thus derived. Using the Monte Carlo simulation method and neural network technique, the distribution type and parameters of the random variable are obtained. Based on the limited failure data, the model can predict the failure probability of arbitrary order for a redundant system, and it can make up for what have been omitted by the traditional models for common cause failure. A typical example is given to illustrate the application of the model with the calculated results compared to those resulting from BFR model. The results show that the proposed approach is more accurate.

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