Results 41 to 50 of about 4,586 (215)

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

Advances in Mechanical Engineering, 2014
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
Shoufeng Tang, Minming Tong, Xinmin He
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Research on classification and identification of mine microseismic signals based on deep learning method

矿业科学学报, 2022
In order to accurately identify mine microseismic signals, this paper proposes a VGG4-CNN deep learning network model suitable for identifying mine microseismic signals. The model is written in Python language and built based on the PyTorch deep learning
Zhao Hongbao, Liu Rui, Liu Yihong, Zhang Yixiao, Gu Tao   +4 more
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Rock falls impacting railway tracks. Detection analysis through an artificial intelligence camera prototype [PDF]

, 2017
During the last few years, several approaches have been proposed to improve early warning systems for managing geological risk due to landslides, where important infrastructures (such as railways, highways, pipelines, and aqueducts) are exposed elements.
Fantini, Andrea, Fiorucci, Matteo, Martino, Salvatore   +2 more
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Recognition of Weak Microseismic Events Induced by Borehole Hydraulic Fracturing in Coal Seam Based on ResNet-10

Applied Sciences, 2023
Borehole hydraulic fracturing in coal mines can effectively prevent coal rock dynamic disasters. Accurately recognizing weak microseismic events is an essential prerequisite for the micro-seismic monitoring of hydraulic fracturing in coal seams.
Yunpeng Zhang, Nan Li, Lihong Sun, Jincheng Qiu, Xiaokai Huang, Yan Li   +5 more
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Nanoseismic monitoring for detection of rockfalls. Experiments in quarry areas [PDF]

, 2018
Le frane per crollo da ammassi rocciosi fratturati sono tra i processi di instabilità gravitativa che più frequentemente interessano opere antropiche quali tagli su versanti naturali o artificiali, pareti di cava, trincee stradali, autostradali o ...
Fiorucci, M., Hakes, C., Iannucci, R., Martino, S., Paciello, A.   +4 more
core   +1 more source

Research on Automatic Classification of Coal Mine Microseismic Events Based on Data Enhancement and FCN-LSTM Network

Applied Sciences, 2023
Efficient and accurate classification of the microseismic data obtained in coal mine production is of great significance for the guidance of coal mine production safety, disaster prevention and early warning.
Guojun Shang, Li Li, Liping Zhang, Xiaofei Liu, Dexing Li, Gan Qin, Hao Li   +6 more
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Automatic picking method of microseismic first arrival time based on improved support vector machine

Gong-kuang zidonghua, 2023
The microseismic first arrival time picking is an important prerequisite for the high-precision positioning of the microseismic source. The traditional manual picking method is inefficient.
LI Tieniu, HU Binxin, LI Huakun, GENG Wencheng, HAO Pengcheng, JI Xubo, SUN Zengrong, ZHU Feng, ZHANG Hua, YANG Chengquan   +9 more
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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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Seismic arrival enhancement through the use of noise whitening [PDF]

, 2017
A constant feature in seismic data, noise is particularly troublesome for passive seismic monitoring where noise commonly masks microseismic events. We propose a statistics-driven noise suppression technique that whitens the noise through the calculation
Belouchrani, Bensen, Birnie, Claire Birnie, Doug Angus, Forghani-Arani, Forghani-Arani, Gambino, Gutenberg, Hom, Kit Chambers, Maxwell, Maxwell, Oye, Roach, Roux, Scharf, Schorlemmer, Staněk, Wang   +19 more
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Mine microseismic signal denoising method and application based on Adaboost_LSTM prediction

Meitan xuebao
Microseismic early warning is of great significance for ensuring mine safety, where a good denoising and accurate P-wave arrival picking of a microseismic signal is fundamental to the reliability of microseismic monitoring. By observing a large amount of
Xueyi SHANG, Yong CHEN, Jie CHEN, Linlin CHEN, Yuanyuan PU   +4 more
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