摘要
简要介绍了轴承故障诊断的基本方法,通过对比共振解调法和经验模态分解法,证明了经验模态分解是一种适用于分析非线性、非平稳信号的方法。同时,通过实际例子验证了该方法可以用于有效地发现轴承故障,从而提高了诊断的准确性。
The basic methods of bearing fault diagnosis were introduced. The empirical mode decomposition method is applicable to analyze non-linear and non-stationary signals in comparison with resonance demodulation methods, which is proved to be effective on fault diagnosis and can improve the accuracy of diagnosis.
出处
《机电工程》
CAS
2007年第10期77-78,90,共3页
Journal of Mechanical & Electrical Engineering
关键词
经验模态分解
故障诊断
非平稳
轴承
empirical mode decomposition （EMD）
fault diagnosis
non-stationary
bearing
