【作者】 王启志； 王晓霞；

【Author】 Wang Qizhi1 Wang Xiaoxia2 (1 College of Mechanical Engineering and Automation, Huaqiao University ,Quanzhou,362021; 2 College of Info Science and Engineering , Huaqiao University ,Quanzhou,362021)

【机构】 华侨大学机电及自动化学院； 华侨大学信息与工程学院；

【摘要】 本文以滚动轴承的故障诊断为例,阐述了模糊C均值聚类在机械故障诊断中的应用。以滚动轴承的故障特征值的聚类中心来评定故障类别收到了良好的效果。与其他方法相比,模糊聚类方法实现只需要少量样本,从而使诊断工作量与诊断时间大为减少。更多还原

【Abstract】 The arithmetic of fuzzy clustering applied to mechanical fault diagnosis is presented. According to the clustering center of Rolling bearing character, a ideal result is get on fault diagnosis. Compared to other method ,fuzzy clustering is more practical, because it only need a few sample. The diagnosis work and time are decreased greatly.更多还原