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Research on Microseismic Signal Denoising Based on ICEEMDAN and Blind Source Separation
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Gang HUANG1, Lulin ZHENG1, Yingle WANG1, Yujun ZUO1, Lujing ZHENG2, Xiaorong LIU1
Mining and Metallurgical Engineering | 2023, 43(3) : 24 - 29
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Mining and Metallurgical Engineering | 2023, 43(3): 24-29
• MINING •
Research on Microseismic Signal Denoising Based on ICEEMDAN and Blind Source Separation
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Gang HUANG1, Lulin ZHENG1, Yingle WANG1, Yujun ZUO1, Lujing ZHENG2, Xiaorong LIU1
Affiliations
  • 1.College of Mining, Guizhou University, Guiyang 550025, Guizhou, China
  • 2.Guizhou Jinfeng Mining Co Ltd, Zhenfeng 562200, Guizhou, China
Published: 2023-06-01 doi: 10.3969/j.issn.0253-6099.2023.03.006
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Microseismic signals collected during roadway construction in Jinfeng Gold Mine in the southwest Guizhou Province are non-stationary and also contaminated with background noise. For solving this problem, a noise reduction method based on the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) combined with blind source separation (BSS) was proposed. With this method, a microseismic signal can be preliminarily decomposed by ICEEMDAN algorithm, and then correlation coefficient and marginal spectrum of signal can be calculated with MATLAB. Components of noise-containing mode and main frequency of signal can be filtered, and FastICA algorithm is finally used for BSS to achieve noise reduction. The practical application in mine shows that compared to empirical mode decomposition (EMD) and traditional wavelet packet threshold method, the proposed method, with higher signal-to-noise ratio (24.142 5 dB), can bring better noise reduction effect with smaller standard error (0.012 18).

ICEEMDAN  /  blind source separation (BSS)  /  FastICA algorithm  /  microseismic signal  /  noise reduction  /  microseismic monitoring
Gang HUANG, Lulin ZHENG, Yingle WANG, Yujun ZUO, Lujing ZHENG, Xiaorong LIU. Research on Microseismic Signal Denoising Based on ICEEMDAN and Blind Source Separation[J]. Mining and Metallurgical Engineering, 2023 , 43 (3) : 24 -29 . DOI: 10.3969/j.issn.0253-6099.2023.03.006
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Year 2023 volume 43 Issue 3
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Article Info
doi: 10.3969/j.issn.0253-6099.2023.03.006
  • Receive Date：2022-12-05
  • Online Date：2026-03-05
  • Published：2023-06-01
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  • Received：2022-12-05
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    1.College of Mining, Guizhou University, Guiyang 550025, Guizhou, China
    2.Guizhou Jinfeng Mining Co Ltd, Zhenfeng 562200, Guizhou, China
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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