基于EEMD_Hankel_SVD的矿山微震信号降噪方法

针对矿山微震信号降噪,提出了一种基于EEMD_Hankel_SVD(集合经验模态分解_Hankel矩阵_奇异值分解)的微震信号降噪方法。首先采用EEMD获得多层模态分量,计算各模态分量与原始信号的相关系数,剔除第一个相关系数差值局部最大值前的模态分量。对剩余各模态分量分别构建Hankel矩阵,再计算各Hankel矩阵的奇异值矩阵。根据奇异值曲线划分信号空间和噪声空间,实现剩余各模态分量的降噪,进而对降噪后的模态分量相加得到降噪信号。仿真试验表明该方法能有效保留信号的局部特征,提高了信噪比;矿山微震信号应用表明该方法有效地提高了STA/LTA,PAI-K和AIC法P波初至拾取效果;仿真试验和矿山微震信号P波拾取均表明该方法降噪效果优于小波重构、EMD重构和Hankel_SVD降噪,且该方法与AIC法结合拾取效果最佳。

Denosing method of mine microseismic signal based on EEMD_Hankel_SVD

To denoise microseismic noises,an EEMD_Hankel_SVD (ensemble empirical mode decomposition_Hankel matrix_signular value decomposition) combined method is proposed.Firstly,the EEMD is used to obtain mode functions,then the correlation coefficient between each mode function and original signal is calculated,and the mode functions before the first local maximum correlation coefficient difference are deleted.The rest mode functions are used to construct Hankel matrixes,and the SVD is applied to decompose the Hankel matrixes.The microseismic signal and noises are divided by the curve of singular values and this is used to denoise mode functions,then the denoised mode functions are combined to obtain denoised microseismic signal.The simulated tests show that the proposed method can retain local features well and increase signal to noise ratio (SNR).The application to mine microseismic signals shows that the proposed method can effectively improve the P-phase picking results of the STA/LTA picker,PAI-K (phase arrival identification-kurtosis) picker and AIC (Akaike information criterion) picker.In addition,both the simulated tests and mine microseismic signal picking results show that the denoising performance of this method is better than that of wavelet reconstruction,empirical mode decomposition (EMD) reconstruction,and Hankel_SVD denoising.Furthermore,the combination with the AIC picker obtains a best picking result.