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The Single-Channel Microseismic Mine Signal Denoising Method and Application Based on Frequency Domain Singular Value Decomposition (FSVD)

Author

Listed:
  • Quanjie Zhu

    (School of Emergency Technology and Management, North China Institute of Science and Technology, Langfang 065201, China)

  • Longkun Sui

    (School of Mine Safety, North China Institute of Science and Technology, Langfang 065201, China)

  • Qingsong Li

    (Guizhou Coal Mine Design & Research Institute, Guiyang 550025, China)

  • Yage Li

    (Science and Technology Innovation Department, China National Coal Group Corp, Beijing 100120, China)

  • Lei Gu

    (School of Mine Safety, North China Institute of Science and Technology, Langfang 065201, China)

  • Dacang Wang

    (School of Mine Safety, North China Institute of Science and Technology, Langfang 065201, China)

Abstract

The purpose of denoising microseismic mine signals (MMS) is to extract relevant signals from background interference, enabling their utilization in wave classification, identification, time analysis, location calculations, and detailed mining feature analysis, among other applications. To enhance the signal-to-noise ratio ( SNR ) of single-channel MMS, a frequency-domain denoising method based on the Fourier transform, inverse transform, and singular value decomposition was proposed, along with its processing workflow. The establishment of key parameters, such as time delay, τ , reconstruction order, k , Hankel matrix length, n , and dimension, m, were introduced. The reconstruction order for SVD was determined by introducing the energy difference spectrum, E, and the denoised two-dimensional microseismic time series was obtained based on the SVD recovery principle. Through the analysis and processing of three types of typical microseismic waveforms in mining (blast, rock burst, and background noise) and with the evaluation of four indicators, SNR , ESN , RMSE , and STI , the results show that the SNR is improved by more than 10 dB after FSVD processing, indicating a strong noise suppression capability. This method is of significant importance for the rapid analysis and processing of microseismic signals in mining, as well as subsequently and accurately picking the initial arrival times and the exploration and analysis of microseismic signal characteristics in mines.

Suggested Citation

  • Quanjie Zhu & Longkun Sui & Qingsong Li & Yage Li & Lei Gu & Dacang Wang, 2023. "The Single-Channel Microseismic Mine Signal Denoising Method and Application Based on Frequency Domain Singular Value Decomposition (FSVD)," Sustainability, MDPI, vol. 15(13), pages 1-22, July.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10588-:d:1187394
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    References listed on IDEAS

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    1. Sandro Andrés & David Santillán & Juan Carlos Mosquera & Luis Cueto-Felgueroso, 2019. "Thermo-Poroelastic Analysis of Induced Seismicity at the Basel Enhanced Geothermal System," Sustainability, MDPI, vol. 11(24), pages 1-18, December.
    2. Dangyu Zhang & Shiqi Liu & Dongyu Guo & Yubao Li & Wenxuan Song & Yiming Wang & Yang Liu, 2023. "Pipe Piles and Key Stratum Modeling for Grouting Reinforcement of Mine Floors under Mining Disturbance and Microseismic Monitoring Evaluation," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
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