基于小波能量谱分析的电机故障诊断

Fault Diagnosis for Electric Motor Based on Wavelet-Energy Spectrum

电机是一种复杂的旋转机械,故障种类多而且难以辨别,利用傅里叶变换对噪声信号分析很难得出满意的结果。为了对小功率异步电机的常见故障进行正确快速地声频诊断,采用小波分析技术对小功率异步电机的几种常见故障噪声进行了多分辨率分析,从能量分布的角度出发,快速且较为准确地诊断出电机故障,诊断效果明显好于傅里叶分析。表明小波分析是对电机故障进行声频诊断的有效方法,同时也提供了一种思路,为电机故障在线实时诊断提供了理论依据。

It is difficult to identify various faults of electric motors by using FFT to analyze the noise signal. This paper introduces wavelet theory and applies it to the common fault diagnosis of micro-power induction motor. Several types of fault noise are analyzed with multi-resolution analysis. The results show that the proposed method has a better performance in rapidity and validity. It also sheds light on further research.