摘要
卫星动量轮具有小子样、长寿命特点,无法进行大样本寿命试验评估可靠性水平,但是可以获得大量的专家经验、地面调试数据等验前信息,因而提出了一种基于贝叶斯网络的动量轮可靠性建模与评估方法。首先,采用贝叶斯网络学习算法,融合各种验前信息,建立动量轮可靠性模型;在此基础上,利用贝叶斯网络推理方法,评估动量轮可靠性,分析动量轮故障;最后通过实例分析表明方法的有效性。
Owing to the long-life and small sample characteristics of the momentum wheel, the large sample life experiments to assess its reliability is carried out. But there is a great deal of prior information obtained from specialists and ground testing, so a new momentum wheel reliability modeling and assessment method using Bayesian network is presented. First, the momentum wheel＇s reliability model is built using various kind of prior information by Bayesian network learning algorithm. Then, the way of assessing the reliability of momentum wheels is provided and the faults is analyzed using the inference algorithm of Bayesian network. Finally, some proper examples are provided to prove the method＇s validity.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2009年第2期484-488,共5页
Systems Engineering and Electronics
关键词
可靠性评估
贝叶斯网络
动量轮
reliability assessment
Bayesian network
momentum wheel
