摘要
介绍了模糊C均值聚类算法在机械故障诊断中的应用。以滚动轴承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。
The arithmetic of fuzzy clustering applied to mechanical fault diagnosis is presented. According to the cluste- ring center of rolling bearing character, a ideal result is get on fault diagnosis. Compared to other method, fuzzy cluste- ring is more practical, because of needing a few sample and much less diagnosis work and time.
出处
《轴承》
北大核心
2008年第10期35-38,共4页
Bearing
基金
福建省自然科学基金资助项目(A0640004)
关键词
滚动轴承
故障诊断
模糊聚类
rolling bearing
fault diagnosis
fuzzy clustering
