基于EMD和ICA的感应电动机故障检测

Fault detection of induction motors based on EMD and ICA

针对感应电动机的转子断条故障和轴承故障,以定子电流信号为研究对象,结合经验模态分解(EMD)和独立分量分析(ICA)原理提出了一种新颖的故障检测方法.该方法首先对定子电流信号进行经验模态分解,去除高频IMF部分,消除噪声干扰;然后用独立分量分析的方法进行特征提取,进而判断故障类型.仿真试验结果表明,该方法用于感应电动机故障诊断是行之有效的.

A new method based on empirical mode decomposition（EMD） and independent component analysis（ICA） is proposed for fault detection of the induction motors.In this paper,the stator currents signals obtained from normal motors and faulty motors are decomposed by EMD.The signal-to-noise ratio（SNR） of the current signals is enhanced by removing the components of intrinsic mode functions（IMFs）in high frequency.Then,ICA is used for extracting the dominating features from the signals to diagnose the fault of induction motors.The experimental results demonstrate that the proposed method can be well applicable for detecting fault of induction motors.