小波-SG-EEMD 混合算法及混沌去噪应用研究

摘要

Since some or all of spectral bands of chaotic signals and those of noise overlap,chaotic signals cannot be extracted effectively from strong disturbances with a single denoising method.Here,the hybrid wavelet-SG-EEMD algorithm was proposed.With the proposed algorithm,the wavelet-Savitzky-Golay(wavelet-SG)algorithm was taken as the pre-filter element of the ensemble empirical mode decomposition(EEMD)in order to reduce the effects of random white noise and local strong disturbances,and then the hydrid algorithm was combined with the characteristics restraining mode mixing of EEMD to extract the chaotic signals from complex and strong disturbances effectively.The implementation of the hybrid filtering algorithm was evaluate with Lorenz time series.Finally,the method was applied in 2-DOF chaotic vibration signals,and the results showed that the strong noise can be filtered normally.%混沌信号和噪声频谱部分甚至全部重叠，单一的去噪方法无法有效地从强干扰中提取有用信号，为此，提出了小波-SG-EEMD 混合去噪算法。该算法将小波-SG 作为 EEMD 的预滤波单元，有效降低白噪声和局部强干扰的影响，并结合 EEMD 抑制模式混叠的特性，可以有效地将混沌信号从复杂干扰中提取出来。利用 Lorenz 时间序列详述了混合滤波算法的实施过程，并将该方法用于两自由度混沌振动信号中。结果表明该方法切实可行，具有非常好的应用价值。