粗糙集和贝叶斯网络融合故障诊断方法

Research on one fusion fault diagnosis method based on rough set theory and bayesian network

融合贝叶斯网络和粗糙集对不确定故障诊断的优势,以及粗糙集对冗余信息的处理能力,给出了一种粗糙集和贝叶斯网络进行融合的装备故障诊断方法,获得最小属性集的贝叶斯网络故障诊断模型及诊断规则,并应用于某型机载电台装备中进行验证,结果表明该方法不仅有效,而且得到的诊断规则也比单纯应用贝叶斯网络要优。

There are uncertain fault diagnosis advantages of Bayesian network and rough sets theory, and rough sets theory also has the processing ability of redundant information, so one fusion fault diagnosis method based on rough sets theory and Bayesian network was given, and the Bayesian Network fault diagnosis model of minimal attribution set and the diagnosis rules were obtained. Then, the method was applied to some aero radio equipment for fault diagnosis, and the results indicated that it was effective and the obtained diagnosis rules was better than the pure Bayesian network rules.