微震信号无参数自动去噪PD算法实现及应用

doi:10.13722/j.cnki.jrme.2017.1151

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Abstract Microseismic signals are often highly corrupted by unwanted noise in engineering. The performance of existing denoising methods depends on the accuracy of selected parameters that need to tune manually. Thus，we have proposed a non-parametric automatic denoising algorithm for microseismic data，named PD method. In this method，we use a modified AIC(akaike information criterion) algorithm to obtain the background noise of the signal，then the noise power spectrum is extracted by Fourier transform in the frequency domain. Next，the noise power spectrum is subtracted from the signal power spectrum，and then we can recover the microseismic signal by inverse Fourier transform. We have tested PD method by synthesized signals with different types and different signal-to-noise ratios using Matlab and compared the result with EEMD and wavelet denoising method. Results show that the mean absolute error and standard deviation of the denoised waveform after PD method are better than that after EEMD and wavelet denoising. For signals with low signal-to-noise ratios，PD method still has a good performance. We have denoised 2 730 microseismic signals recorded by a microseismic monitoring system in Qinling No.4 inclined shaft of Shaanxi Yinhanjiwei project，China. The average P-wave signal-to-noise ratio is increased from 16.49 to 35.62 after PD method denoising. The results show the effectiveness of the proposed method for improving microseismic data quality.

Key words： earthquake engineering microseismic monitoring signal denoising P-wave arrival picking PD method

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	Articles by authors
	PENG Ping?an1
	2
	WANG Liguan1
	2
	PEI Anlei2

Cite this article:

PENG Ping?an1,2,WANG Liguan1, et al. Non-parametric automatic microseismic data denoising via PD method and its application[J]. , 2019, 38(S1): 3061-3069.

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https://rockmech.whrsm.ac.cn/EN/10.13722/j.cnki.jrme.2017.1151 OR https://rockmech.whrsm.ac.cn/EN/Y2019/V38/IS1/3061

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