基于CEEMDAN和小波变换的地震信号随机噪声压制新方法

提出一种结合自适应噪声完备集合经验模态分解（CEEMDAN）和小波变换（WT）的地震信号去噪新方法CEEMDAN-WT。首先利用CEEMDAN将地震信号自适应地分解为若干个固有模态函数（IMF）和余量；然后计算各分量与原始信号的皮尔森相关系数，对处在不同相关系数阈值区间内的分量分别作小波滤波、维持原状及直接剔除等处理，并进行线性重构；最后构建样本熵变化量、互信息、信噪比等指标体系，定量评估去噪效果。模拟实验与实测数据（青海玛多地震）计算结果表明，与EMD、EEMD等方法相比，CEEMDAN-WT方法能有效抑制随机噪声的影响，提高信噪比，并且地震信号的精细化重构效果较好，信号有效成分得到较大保留。

A New Random Noise Attenuation Method of Seismic Signal Based on CEEMDAN and Wavelet Transform

We propose a seismic signal denoising method combining adaptive noise complete ensemble empirical mode decomposition(CEEMDAN) and wavelet transform(WT). First, using CEEMDAN, we adaptively decompose the seismic signal into several intrinsic mode functions(IMFs) and margins, and calculate the Pearson correlation coefficient between each component and the original signal. We process the components in the threshold interval by wavelet filtering, maintaining the original state, and directly eliminating, and then we carry out linear reconstruction. Finally, to quantitatively evaluate the denoising effect, we construct the index system of sample entropy change, mutual information, and signal-to-noise ratio. The simulated experiment and measured data (Maduo earthquake in Qinghai) results show that, compared with EMD, EEMD and other methods, the CEEMDAN-WT method can effectively suppress the influence of random noise and improve the signal-to-noise ratio. The refined reconstruction effect of the seismic signal is better, and the effective components of the signal are largely preserved.