基于EMD和Hilbert包络谱的滚动轴承故障诊断  

Fault Diagnosis of Rolling Bearings Based on EMD and Hilbert Envelope Spectrum

作　　者：石文磊[1] 陈兴明[1] 袁海龙[1] 

机构地区：[1]解放军理工大学工程兵工程学院,江苏南京210007

出　　处：《机械工程与自动化》2010年第5期108-110,113,共4页Mechanical Engineering & Automation

摘　　要：为了对旋转机械中滚动轴承的运行状态进行故障监测和诊断,提出了一种基于EMD和Hilbert包络谱的滚动轴承故障诊断新方法。通过在滚动轴承实验台上提取振动信号,用EMD对数据进行分解得振动信号的固有模态函数分量(IMF分量),然后对IMF作Hilbert包络并进行谱分析。结果表明,该方法能够准确地识别和诊断出滚动轴承的运行状态和故障类型,非常适合滚动轴承故障精确诊断,具有很高的工程实用价值。For monitoring and diagnosing fault of roller bearing of rotating machinery, a new method was presented by combining empirical mode decomposition （EMD） with Hilbert envelope spectrum on the basis of the collection and disposal of roller bearing vibration signals. Having experimented on the roller bearings lab-table and analyzed the data by using EMD, then made the Hilbert envelope spectrum of intrinsic mode functions （IMFs）, the result shows that it can identify and diagnose not only the running states but also the fault types exactly. So the method suits for the fault diagnosis of roller bearing, and is of a practical value.

关 键 词：经验模态分解(EMD) 内禀模态函数(IMF) 故障诊断 Hilbert包络谱 滚动轴承 

分 类 号：TH133.33[机械工程—机械制造及自动化] TH165.3