Results 21 to 30 of about 5,383,519 (211)
Frontiers in Earth Science, 2022 Microseismic events can be used to analyze the risk of tunnel collapse, rock burst, and other mine hazards in space and time. In practice, the artificial activities and other signals at the mining site can seriously interfere with the microseismic ...
Da Zhang +6 more
semanticscholar +3 more sources
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
openaire +3 more sources
Research on Feature Fusion Method of Mine Microseismic Signal Based on Unsupervised Learning
Shock and Vibration, 2021 The feature extraction of high-precision microseismic signals is an important prerequisite for multicategory recognition of microseismic signals, and it is also an important basis for intelligent sensing modules in smart mines.
Rui Liu
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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 ...
Tao Song +5 more
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Automatic P-Phase-Onset-Time-Picking Method of Microseismic Monitoring Signal of Underground Mine Based on Noise Reduction and Multiple Detection Indexes. [PDF]
Entropy (Basel), 2023 The underground pressure disaster caused by the exploitation of deep mineral resources has become a major hidden danger restricting the safe production of mines. Microseismic monitoring technology is a universally recognized means of underground pressure
Dai R, Wang Y, Zhang D, Ji H.
europepmc +2 more sources
A Nonparametric Method for Automatic Denoising of Microseismic Data
Shock and Vibration, 2018 Noise suppression or signal-to-noise ratio (SNR) enhancement is often desired for better processing results from a microseismic dataset. In this paper, we proposed a nonparametric automatic denoising algorithm for microseismic data.
Pingan Peng, Liguan Wang
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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.
Wenjin Yan +8 more
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Classification of Microseismic Signals Using Machine Learning
ProcessesThe classification of microseismic signals represents a fundamental preprocessing step in microseismic monitoring and early warning. A microseismic signal source rock classification method based on a convolutional neural network is proposed.
Yi Cui +6 more
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Microseismic monitoring of an unstable rock face - Preliminary signal classification
Proceedings, 2015 We analyse signals collected by a microseismic monitoring network installed on an unstable rock face threatening the city of Lecco, in the North of Italy. We propose a classification process based on parameters computed in both time and frequency domains
D. Arosio +10 more
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