摘要
针对水泵电机轴承故障振动信号噪声大和非平稳性的特点,提出了基于经验模态分解的诊断方法;通过对原始信号进行经验模态分解,得到包含故障特征的固有模态分量,从而可以提取出故障频率。该方法应用于外圈、内圈和滚动体故障诊断,取得了很好效果。
Aim at the signals of water-pump motor, which are of high noise and nonstationarity, the paper proposes a fault diagnosis method for the rolling bearing based on empirical mode decomposition （EMD）. The method uses the first intrinsic mode functions （IMF） separated by EMD to extract faulty frequencies of the bearing. Effectiveness of the method is proven to the inner race, outer race and the rolling parts fault.
出处
《制冷空调与电力机械》
2005年第4期81-83,共3页
Refrigeration Air Conditioning & Electric Power Machinery
基金
三峡大学科学基金资助项目。
关键词
经验模式分解
固有模式分量
滚动轴承
故障诊断
empirical mode decomposition （EMD）
intrinsic mode functions （IMF）
rolling bearing
fault diagnosis
