EMD方法在烟机摩擦故障诊断中的应用

提出了一种将经验模式分解（Empirical Mode Decomposition，简称EMD）方法与传统信号处理技术相结合的故障诊断方法。首先将原始信号分解为若干基本模式分量（Intrinsic Mode Functions，简称IMFs），通过希尔波特变换得到每个IMF相应的瞬时频率，再对此瞬时频率曲线做傅里叶变换得到其频谱图，该频谱图即表示了对应IMF的调频频率。利用对应IMF组合成基于EMD的滤波轴心轨迹，这种轴心轨迹可以准确反映轴心的实际运行状况。将该方法应用于某炼油厂烟机摩擦故障诊断中，发现摩擦故障信号具有有色噪声分量存在、工频IMF的调频现象和基于EMD轴心轨迹的反转现象等特征。结果表明提出的方法在旋转设备摩擦故障诊断中非常有效。

Application of Empirical Mode Decomposition Method to Friction Fault Diagnosis for Gas Turbo

A combined fault diagnosis method based on Empirical Mode Decomposition (EMD) method and traditional signal processing technique was proposed. With this method, the original signal was decomposed into several Intrinsic Mode Functions (IMFs) with EMD, the instantaneous frequency of each IMF was obtained with Hilbert transform, and the spectrum of the instantaneous frequency was accordingly calculated with Fast Fourier Transform (FFT), where the spectrum represented the modulation frequency of corresponding IMF; the EMD-based orbit was formed with corresponding IMFs, and it exactly expressed the running condition of axis. The proposed method was applied to friction fault diagnosis for gas turbo in an oil refinery. The characters of friction fault signals, such as colored noise, modulation of operating frequency IMF and reversal of EMD-based orbit were found. The results show that the proposed method is effective in friction fault diagnosis for rotating equipment.