基于小波包和主成分分析的滚动轴承状态振动监视方法

Rolling Bearing Condition Vibration Monitoring Based on Wavelet Packet and Principal Component Analysis

摘要:

针对滚动轴承早期故障状态难以监测的现状,文章采用小波包及主成分分析法对滚动轴承振动信号进行分析,提出了一种综合振动能量指标,用于监视滚动轴承状态。采用滚动轴承实验数据对该方法有效性进行了验证,结果表明:该方法构建的综合振动能量指标能够有效发现滚动轴承早期故障,对早期故障程度反应能力强,优于一些其他传统的监视指标。

Abstract:

According to the fact that the early fault state of rolling bearing is difficult to monitor, the wavelet packet decom?position and principal component analysis were used to analyze the vibration signals of rolling bearing, and a comprehen?sive vibration energy index for monitoring the status of rolling bearing was proposed. The experimental data of rolling bear?ing were used to verify the effectiveness of the method, and the results showed that the integrate vibration energy index con?structed by the method could effectively find the early fault of rolling bearings, and had a strong reaction capability to theearly fault, which outperformed the other traditional monitor indices.