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Automatic detection of arrival time for noisy microseismic data using a transformed difference between multiwindow energy ratios method [PDF]
Scientific ReportsDetection of arrival times of microseismic events is one of the most fundamental steps in the application of microseismic monitoring. However, accurately determining arrival time remains challenging due to low signal-to-noise ratio and the complexity of ...
Zhiyong Zhang +7 more
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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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Dynamic model of microseismic signal transformation
Mining Journal of Kryvyi Rih National UniversityA.V. Bakai, B.I. Rybalko
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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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Enhancing Microseismic Signal Classification in Metal Mines Using Transformer-Based Deep Learning
Sustainability, 2023 As microseismic monitoring technology gains widespread application in mine risk pre-warning, the demand for automatic data processing has become increasingly evident. One crucial requirement that has emerged is the automatic classification of signals. To
Pingan Peng, Ru Lei, Jinmiao Wang
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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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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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Wavelet Transform-Based Fuzzy Clustering Microseismic First-Arrival Picking Method
IEEE Access, 2023 Microseismic arrival time picking serves as the foundation for microseismic source localization and holds significant importance in the field of microseismic monitoring.
Tingting Lin +3 more
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