【摘要】 基于经验模态分解(Empirical Mode Decomposition,EMD)的希尔伯特变换(Hilbert Transformation,HT),是先把一列时间序列数据通过经验模态分解成本征模函数(Intrinsic Mode Function,IMF),然后经过希尔伯特变换获得瞬时频率的信号处理方法。针对HT求瞬时频率的不足,提出了把IMF分解成包络和纯调频信号,然后通过对纯调频信号进行反余弦求瞬时频率的新方法。通过对非线性仿真信号研究表明,该方法是有效的。把该方法应用于转子横向裂纹的时频分析,表明能把横向裂纹转子的扭振所形成的相位调制现象检测出来,获得了良好的效果。仿真和实测信号的分析结果说明,用新方法对振动信号进行时频分析是有效的。该研究成果能广泛地用于信号时频分析领域。更多还原

【Abstract】 A new method for identifying the instantaneous frequency with empirical mode decomposition (EMD) based Hilbert transformation (HT) was proposed. Through EMD,the time series data are seperated into intrinsic mode functions (IMFs), and then each IMF is decomposed to an envelope signal and a frequency modulated signal. The instantaneous frequency can be derived from the frequency modulated signal using arccosine function. A simulated nonlinear signal was processed using the method and the results show the validity of the technology. A deep crack rotor vibration signal was dealt with as an example and the results show that the method is helpful to detect the phase-modulation caused by torsional vibration of the rotor.更多还原