Anomalies of low-intensity acoustic wave attenuation in rocks

Машинский, Э. И.

doi:10.1007/s10913-008-0038-6

Cited by 5 publications

(1 citation statement)

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“…When the fracture reaches approximately half its breaking strength, a range of crevasses starts to appear and produces high energy level AE called "microseisms. " To a certain extent, the intensity and frequency of microseisms and AE reflect the stress state and deformation energy release rate of a coal rock mass [1][2][3][4][5]. The monitoring of microseisms began in the 1990s.…”

Section: Introductionmentioning

confidence: 99%

The Optimum Wavelet Base of Wavelet Analysis in Coal Rock Microseismic Signals

Tang

Tong

2014

Advances in Mechanical Engineering

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Coal rock rupture microseismic signal is characterized by time-varying, nonstationary, unpredictability, and transient property. Wavelet transform is an important method in microseismic signals processing. However, different wavelet bases yield different results when analyzing the same signal. To study the comparability of different wavelet bases in analyzing microseismic signals, the current paper uses the microseismic signals released from coal rock bursting as the research subject. Through the analysis of the properties of commonly used wavelet basis functions and the characteristics of coal rock microseismic signals, the current study found that Coiflet and Symlet wavelets are suitable for analyzing coal rock microseismic signals. Sym 8 and Coif 2 wavelets were found to be suitable for analyzing and denoising coal rock microseismic signals. After Sym 8 wavelet denoising, signal-to-noise ratio (SNR) and the root mean square error were 30.4184 and 1.3109 − 07, respectively. After Coif 2 wavelet denoising, the SNR and the root mean square error values were 35.2176 and 1.0312 − 07, respectively. The results will aid in the analysis and extraction of coal rock microseismic signals.

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