摘要
针对复杂机械系统,提出了基于Copula贝叶斯网络(CBN,Copula Bayesian Network)模型的可靠性分析方法。由于复杂机械系统变量多,相互之间存在相关性,传统可靠性方法在相关性和推理性分析存在不足,而CBN模型兼有Copula函数和贝叶斯网络的优点,在考虑变量之间相关性的同时,能够依据贝叶斯网络进行可靠性概率推断。将BN转换成CBN拓扑结构,通过各个节点的边缘分布以及相关系数矩阵,构建局部t-Copula函数,实现多变量高维度表现,并利用网络的推断能力,通过已知节点失效概率推导其他节点失效概率。最后以海工平台双啮合抬升减速器为研究对象,构建CBN模型,得到各个节点之间相关结构,并进行概率推断,得到减速箱失效概率,计算结果与传统BN模型方法相比趋于保守,在实际工程上更偏安全。
A reliability analysis method for complicated mechanical system is proposed which is based on Copula Bayesian network. Since the variables in complicated mechanical system are numerous and correlated to each other,the traditional analysis methods are incapable to solve the problems. However,the Copula Bayesian network takes advantage of both Copula function and Bayesian network,it can takes the correlation of variables into consideration by using Copula function,and makes probability inference of reliability at the same time. The CBN structure was transformed from BN at first,and then local t-Copulas were modeled based on the marginal distributions and correlation coefficient matrix of variables. The reliability of an jack-up gearbox was analyzed by CBN,and the correlated structure of nodes was obtained. The failure probability of gearbox was calculated by CBN,and the result showed that it was more secure and accurate than the traditional BN method.
出处
《机械强度》
CAS
CSCD
北大核心
2018年第1期88-94,共7页
Journal of Mechanical Strength
基金
上海市科委科技创新行动计划(17DZ1204602)
国家自然科学基金项目(51205292)资助~~
关键词
CBN模型
相关性
多元变量
抬升减速器
可靠性
CBN model
Correlation
Multivariate variables
Jack-up gearbox
Reliability
