摘要
针对船舶汽轮机滑油系统特点,提出了基于马尔科夫过程的动态贝叶斯网络方法;针对不同类型的马尔科夫过程,分别建立了其动态贝叶斯网络模型,给出了参数确定方法;通过对某汽轮机滑油系统管路进行分析,证明了方法的正确性和优势,相比于马尔科夫过程,动态贝叶斯网络更加适合于汽轮机等复杂系统安全性分析。
According to the characteristics of oil system, in steam tuibine of ship, this paper presents a Dynamic Bayesian Networks method based on Markov Chain. The Dynamic Bayesian Networks models are built correspond to disfferent types of markov process. The methods are proposed to assess parameters of models. The results show the validity and advantages of proposed method, which is applied into oil canal system of steam turbine. Comparing with markov process, the Dynamic Bayesian Networks method is more suitable to safety analysis in steam turine.
出处
《汽轮机技术》
北大核心
2017年第5期361-364,共4页
Turbine Technology
基金
武器装备预研基金(9140A27030514JB11449)
