模糊集之间的相似度量在汽轮发电机组故障诊断中的应用  

The Application of Similarity Measure between Fuzzy Sets to Fault Diagnosis of Steam Turbine-generator Sets

作　　者：乔晓利[1] 叶军[1] 柳春平[1] 李伟波[1] 

机构地区：[1]绍兴文理学院机电系,浙江绍兴312000

出　　处：《机床与液压》2006年第12期219-220,229,共3页Machine Tool & Hydraulics

摘　　要：描述了模糊集之间的相似度量法,并应用于汽轮发电机组故障诊断中。模糊集之间的相似度量是指故障测量数据集与故障标准数据集之间的相似度量,这种故障诊断方法的本质是故障类型的模式识别,相似度量值越大,那么这种类型故障的可能性就越大。通过实例阐明本方法在汽轮发电机组故障诊断中的应用是可行的。The method of similarity measure between fuzzy sets was described and was applied in the fault diagnosis of steam turbine - generator sets. The similarity measure between fuzzy sets is the similarity measure between fault measure data sets and fault standard data sets. The essence of this fault diagnosis method is a pattern identification of fauh types. The bigger the similarity measuring value of fault pattern identification is, the bigger the possibility of the fault is. An example explains that the application of similarity measure between fuzzy sets to fault diagnosis of steam turbine - generator sets is feasible.

关 键 词：模糊集 相似度量 故障诊断 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]