A method for blasting vibration signal denoising based on ensemble empirical mode decomposition-wavelet threshold
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摘要: 为了更好地消除混杂在爆破信号中的噪声，引入一种基于集合经验模态分解和小波阈值共同作用的降噪方法。首先将信号进行集合经验模态分解，然后选择含噪的模态函数分量进行小波阈值降噪处理，最后把处理后的分量和未处理的分量进行叠加，重构的信号即为降噪信号。该方法不仅能有效的去除噪声，还能使爆破波形保留其真实性和完整性。Abstract: In this work we proposed a method based on ensemble empirical mode decomposition (EEMD) and wavelet threshold for eliminating the noise contained a in blasting signal. Following this method, the signal is firstly decomposed using the ensemble empirical mode decomposition; then, the intrinsic mode function with noise is processed by the wavelet threshold denoising; and, finally, the processed signal is superimposed on the untreated component of the signal, and the signal thus reconstructed is the denoised signal. This method can not only can effectively remove the noise, but also enable the burst wave form to retain its authenticity and integrity
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Key words:
- blasting signal /
- ensemble empirical mode decomposition /
- wavelet threshold /
- denoising
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图 8 降噪前、后的信号三维图
Figure 8. Three dimensional signal by EEMD-wavelet threshold method before and after denoising
表 1 互相关系数对应表
Table 1. Cross correlation coefficient
互相关系数 IMF分量 x1 x2 x3 x4 x5 x6 x7 x8 x9 R1 0.057 - - - - - - - - R2 - 0.167 - - - - - - - R3 - - 0.580 - - - - - - R4 - - - 0.774 - - - - - R5 - - - - 0.623 - - - - R6 - - - - - 0.264 - - - R7 - - - - - - 0.064 - - R8 - - - - - - - 0.001 - R9 - - - - - - - - 0.000 
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表 2 信号降噪指标
Table 2. Signal denoising index
降噪方法 ξ/dB ε/10-10 EEMD-小波阈值 26.07 1.30 EEMD 23.11 2.68 小波阈值 21.12 4.23
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