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。
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 the early fault,which outperformed the other traditional monitor indices.
作者
胡强
张赟
庹酉东
周强
HU Qiang;ZHANG Yun;TUO Youdong;ZHOU Qiang(Equipment Project Manage center of Naval Equipment Department,Beijing 100071,China;Naval Aviation University,Yantai Shandong 264001,China;The 91486th Unit of PLA,Lingshui Hainan 572400,China)
出处
《海军航空工程学院学报》
2020年第3期265-270,284,共7页
Journal of Naval Aeronautical and Astronautical University
基金
国家自然科学基金资助项目(51505492)。
关键词
滚动轴承
小波包
主成分分析
状态监视
rolling bearing
wavelet packet
principal component analysis
condition monitoring
作者简介
胡强(1983-),男,工程师,硕士。
