感应电机轴承故障检测方法研究

Fault Detection of Induction Motor Bearing

分析了感应电机轴承发生故障时的振动信号的特性,利用带通滤波器和希尔伯特变换,对感应电机轴承振动信号进行处理,然后采用高分辨率谱估计算法——MU S IC(M u ltip le S igna l C lass ification)算法对包络信号作谱分析,再从包络信号的MU S IC谱中提取故障特征频率分量。研究结果表明,该方法频率分辨率更高,故障检测更为准确。将该方法应用于电机轴承故障诊断,可准确提取轴承故障特征分量。

The feature of vibration signal of defective rolling bearing is analyzed,the band pass digital filter and Hilbert transform are used in processing the vibration signal of induction motor bearing,and then the MUSIC(multiple signal classification) algorithm is used for analyzing the envelope signal.Faults of rolling bearing are diagnosed by extracting fault characteristic frequency from MUSIC spectrum of envelope signal.The experimental results show that the fault characteristic components can be obtained accurately through the method presented in this paper when bearing faults in induction motors occur,and the feasibility of the method is confirmed.