Results 41 to 50 of about 615 (171)

An optimizing microseismic method for rock burst early warning based on mining production process

Deep Underground Science and Engineering, EarlyView.
A classification early warning method of rock burst based on hourly microseismic data is proposed, which can be combined with the on‐site production process to provide more timely warning. Abstract Microseismic (MS) events have been reported in nearly every coal mining country, which could well lead to rock burst in underground coal mines.
Zepeng Han, Linming Dou, Wu Cai, Mingbo Chi, Guojun Xi, Shuai Chen, Biao Jiao   +6 more
wiley   +1 more source

First-Arrival Picking for Microseismic Monitoring Based on Deep Learning

International Journal of Geophysics, 2021
In microseismic monitoring, achieving an accurate and efficient first-arrival picking is crucial for improving the accuracy and efficiency of microseismic time-difference source location.
Xiaolong Guo
doaj   +1 more source

Fracture evolution of a thick soft protection layer and the water inrush mechanism in overburden under longwall mining

Deep Underground Science and Engineering, EarlyView.
Through shear–tensile creep tests and viscoelastic modeling, the fracture evolution of thick soft protective layers is clarified. Results show thickness‐dependent rheological failure modes that govern four types of roof water inrush, providing a mechanism‐based framework for hazard prediction and control. Abstract In the Jurassic coal‐bearing strata of
Mengnan Liu, Wei Qiao, Xianggang Cheng, Xiangsheng Meng, Peichao Feng   +4 more
wiley   +1 more source

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

Deep Underground Science and Engineering, EarlyView.
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li, Huiyong Yin, Fangying Dong, Tao Wu, Chao Zhang   +4 more
wiley   +1 more source

Siamese Unsupervised Clustering For Removing Uncertainty In Microseismic Signal Labelling

IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
The labelling of large seismic datasets is a challenging problem. Currently the methods most favoured by geoscientists are based on well known geophysical properties with STA/LTA ratio pickers remaining highly trusted to generate results which can be quickly attributed due to their ability to pick relatively high Signal to Noise Ratio (SNR) events with
Murray, David, Stankovic, Lina, Stankovic, Vladimir   +2 more
openaire   +3 more sources

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

Deep Underground Science and Engineering, EarlyView.
This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu, Dawei Cui, Yingjie Liu, Yuntao Liang, Yue Zhang   +4 more
wiley   +1 more source

Research on Multi-Class and Weak Signal Recognition of Microseismic Events Based on an Optimized U-Net Model

Applied Sciences
Microseismic monitoring is essential for the early warning of mine dynamic disasters; however, weak signal characteristics and strong environmental noise often lead to missed detections and false alarms.
Guangdong Song, Zunting Wang, Jiulong Cheng, Feng Zhu, Jiqiang Wang, Moyu Hou   +5 more
doaj   +1 more source

Mechanism of “seesaw‐type” rock burst in coal seam mining beneath mountainous areas

Deep Underground Science and Engineering, EarlyView.
This study reveals the mechanism of “seesaw‐type” rock bursts during coal mining beneath mountainous areas. The advancing working face induces nonuniform fracturing of the overburden. The detached mountain mass then undergoes a seesaw‐type rotational movement around a shifting pivot, driving the primary fracture through a characteristic “open‐close ...
Chao Zhou, Xueqiu He, Zhenlei Li, Ping Wang, Dazhao Song, Fuxing Jiang, Shan Yin, Anliang Lü, Menghan Wei, Taoping Zhong   +9 more
wiley   +1 more source

Exponentially‐constrained Gaussian mixture model for quantifying vertical development of water‐conducting fracture zones in lithologically stratified mining roofs

Deep Underground Science and Engineering, EarlyView.
This study proposes an exponentially‐constrained Gaussian mixture model (EcGMM) to quantify vertical fracture heterogeneity in stratified roof strata. The model integrates a piecewise exponential decay term capturing global stress dissipation with Gaussian components representing localized fracture intensification at lithological interfaces.
Huiqing Yuan, Zhimin Xu, Weixiao Chen, Chenghang Zhang, Shijie Xiong, Yajun Sun   +5 more
wiley   +1 more source

Seismic Tremor as a Precursor to Hydrothermal Explosions Near Mutnovsky Volcano (Kamchatka)

Geophysical Research Letters, Volume 53, Issue 15, 16 August 2026.
Abstract Mutnovsky Volcano, ∼70 km SW of Petropavlovsk‐Kamchatsky, exhibits persistent degassing, hosts active hydrothermal springs and the Mutnovsky Geothermal Power Plant (MGPP) on its slopes. Using the network covariance matrix approach, we analyzed seismic data recorded in 2023–2024 by 15 seismic stations operating around Mutnovsky Volcano.
Y. Berezhnev, N. Belovezhets, N. M. Shapiro, S. Abramenkov, I. Abkadyrov, S. Yaskevich, D. Chebrov, I. Koulakov   +7 more
wiley   +1 more source