A Synthetic Solution for Identification and Extraction of the Effective Microseismic Wave Component Using Decomposition on Time, Frequency, and Wavelet Coefficient Domains

Mingwei Zhang, Qingbin Meng, Shengdong Liu, Hideki Shimada

研究成果: Contribution to journalArticle査読

抄録

To reduce noise components from original microseismic waves, a comprehensive fine signal processing approach using the integrated decomposition analysis of the wave duration, frequency spectrum, and wavelet coefficient domain was developed and implemented. Distribution regularities of the wave component and redundant noise on the frequency spectrum and the wavelet coefficient domain were first expounded. The frequency threshold and wavelet coefficient threshold were determined for the identification and extraction of the effective wave component. The frequency components between the reconstructed microseismic wave and the original measuring signal were compared. The noise elimination effect via the scale-changed domain decomposition was evaluated. Interaction between the frequency threshold and the wavelet coefficient threshold in the time domain was discussed. The findings reveal that tri-domain decomposition analysis achieves the precise identification and extraction of the effective microseismic wave component and improves the reliability of waves by eliminating the redundant noise. The frequency threshold and the wavelet coefficient threshold on a specific time window are two critical parameters that determine the degree of precision for the identification of the extracted wave component. This research involves development of the proposed integrated domain decomposition method and provides a diverse view on the fine processing of the microseismic signal.

本文言語英語
論文番号3875170
ジャーナルShock and Vibration
2017
DOI
出版ステータス出版済み - 2017

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Condensed Matter Physics
  • Geotechnical Engineering and Engineering Geology
  • Mechanics of Materials
  • Mechanical Engineering

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