摘要
针对设备故障诊断技术中存在的固有不确定性问题,通过分析传统故障树模型存在的局限性以及传统贝叶斯网络建造困难的特点,提出了一种融合于故障树和传统贝叶斯网络的新方法—诊断贝叶斯网络法,并阐述了故障树和贝叶斯网络的故障诊断策略优化方法的基本思想和具体算法.通过综合分析故障树和贝叶斯网络在诊断推理和模型表达方面的特点得出,新方法可使二者充分发挥优势,有效解决故障诊断中存在的不确定性问题,提高了诊断的准确率,在故障诊断领域中具有一定的实际应用价值.
Aiming at the intrinsical uncertainty in fault diagnosis, a diagnostic Bayesian networks method integrated with fault tree （FT） and Bayesian networks （BN） was proposed through analyzing the limitation of traditional fault tree model and the difficulty in constructing traditional Bayesian networks. The basic principle and algorithm of fault diagnosis strategy optimization method of fault tree and Bayesian networks were expatiated. Through evaluating the characteristic of fault tree and Bayesian networks in the diagnosis inference and model expression, it is demonstrated that the new method can take the advantages of fault tree and Bayesian networks and solve the uncertain problems in fault diagnosis availably and exactly. The new method has the actual application value in the fault diagnosis field.
出处
《沈阳工业大学学报》
EI
CAS
2009年第4期454-457,共4页
Journal of Shenyang University of Technology
基金
沈阳工业大学博士启动基金资助项目(521101302)
关键词
故障诊断
不确定性
故障树
贝叶斯网络
融合
诊断贝叶斯网络
策略优化
诊断推理
模型表达
fault diagnosis
uncertainty
fault tree
Bayesian networks
integration
diagnostic Bayesiannetworks
strategy optimization
diagnosis inference
model expression
