摘要
基于经验模态分解(EmpiricalModeDecomposition,EMD)的希尔伯特变换(HilbertTransformation,HT),是先把一列时间序列数据通过经验模态分解,然后经过希尔伯特变换获得频谱的信号处理新方法。介绍了该方法的理论和算法。对仿真和旋转机械油膜涡动故障振动信号分别用基于EMD的HT和基于STFT(Short-TimeFourierTransforma tion,STFT)的时频分析进行了比较研究,研究结果说明,用基于EMD的HT方法对旋转机械的振动信号进行时频分析比STFT有效。
The method of empirical mode decomposition (EMD) based Hilbert Transformation(HT) is that, first, separate the series data to components with different time scale, say, intrinsic mode function (IMF), using EMD, then apply the Hilbert transformation to every IMFs. The result is the time-frequency spectrum of the data. The method and algorithm was explained in detail. Emulation and oil film whirling vibration signals were analyzed using the method. After applied Hilbert transformation to the signals' IMFs, the time-frequency spectrums were obtained. The Shorttime Fourier Transformation(STFT) method was applied to the signals also. Compared the two time-frequency method. The EMDbased HT timefrequency analysis of the vibration signal is more sharp and clear than the STFTbased's, and the STFTbased's frequencies were confused. The conclusion was deduced that the EMDbased HT timefrequency analysis method is better than the STFTbased's in the field of vibration signals' processing in rotating machinery.
出处
《汽轮机技术》
北大核心
2002年第6期336-338,共3页
Turbine Technology
基金
浙江省自然科学基金项目(5001004)资助。
