Results 11 to 20 of about 4,586 (215)
Identification of Microseismic Signals Based on Multiscale Singular Spectrum Entropy
Shock and Vibration, 2020 The accurate identification of effective microseismic events has great significance in the monitoring, early warning, and forecasting of rockburst hazards.
Xingli Zhang +3 more
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Energies, 2023 Microseismic monitoring has become a well-known technique for predicting the mechanisms of rock failure in deeply buried energy exploration, in which noise has a great influence on microseismic monitoring results.
Shibin Tang +4 more
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Parallel Processing Method for Microseismic Signal Based on Deep Neural Network
Remote Sensing, 2023 The microseismic signals released by rock mass fracture can be captured via microseismic monitoring to evaluate the development of geological disasters.
Chunchi Ma +7 more
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CNN-Transformer for Microseismic Signal Classification
Electronics, 2023 The microseismic signals of coal and rock fractures collected by underground sensors contain masses of blasting vibration signals generated by coal mine blasting, and the waveforms of the two signals are highly similar. In order to identify the true microseismic signals with a microseismic monitoring system quickly and accurately, this paper proposes a
Xingli Zhang +3 more
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Shock and Vibration, 2021 The research on charge induction and microseismic characteristics of coal and rock under different loading rates is of great significance for rockburst prediction. In this study, the coal and sandstone samples from the No.
Yuchun Liu +4 more
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Sensors, 2021 Due to the complexity of the various waveforms of microseismic data, there are high requirements on the automatic multi-classification of such data; an accurate classification is conducive for further signal processing and stability analysis of ...
Hang Zhang +5 more
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Microseismic Signal Classification Based on Artificial Neural Networks
Shock and Vibration, 2021 The classification of multichannel microseismic waveform is essential for real‐time monitoring and hazard prediction. The accuracy and efficiency could not be guaranteed by manual identification. Thus, based on 37310 waveform data of Junde Coal Mine, eight features of statistics, spectrum, and waveform were extracted to generate a complete data set. An
Chong-wei Xin +2 more
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Analysis of rock microseismic signal based on blind source wavelet decomposition algorithm
AIP Advances, 2022 At present, microseismic technology is a widely used method for monitoring the rock burst phenomenon during the construction of deep-buried tunnels. The rock fracture in the tunnel will generate seismic waves.
Guili Peng +4 more
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Research on microseismic event imaging based on waveform clustering analysis
矿业科学学报, 2022 The quality of microseismic data greatly affects the accuracy of the source location results, especially in surface microseismic data where the first arrivals of P waves and S waves are not obvious or the low signal-to-noise ratio signals are difficult ...
Li Dewei, Yang Ruizhao, Meng Lingbin
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Remote Sensing, 2023 Numerous microseismic signals are produced by rock mass fracture during earthquakes, geological disasters, or underground excavations. Moreover, a large amount of noise signals are captured during microseismic signal monitoring.
Chunchi Ma +8 more
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