摘要
为了对旋转机械内轴承的运行状态进行故障监测和诊断,在对振动冲击信号进行分段截取的基础上,提出了基于分段信号时、频域特征提取结合模糊K聚类的滚动轴承故障诊断方法,并将该方法应用于NU205轴承故障诊断中.
In order to monitor and diagnose the fault of the bearings＇ running state in the rotating machinery,a method of rolling bearing fault diagnosis based on the frequency domain feature extraction and fuzzy K clustering of sub -signals was proposed, which is on the basis of the interception on the vibration acceleration signal. The method was applied to fault diagnosis of bearings NU205.
出处
《机械与电子》
2011年第12期3-5,共3页
Machinery & Electronics
基金
云南省教育厅科学研究基金资助项目(2010Y380)
关键词
故障诊断
特征提取
模糊聚类分析
滚
动轴承
fault diagnosis
feature extraction
K - clustering
roiling bearing
