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Full-Text Articles in Mining Engineering
Application Of Integrated Geophysical Surveys In The Identification Of Hidden Fire Sources In Spontaneous Combustion Zones In Coal Seams, Ma Zijun, Yang Haiyan, Li Wenyu, Xu Yunlei, He Yunlan, Liu Zhuoming, Li Peng, Huang Jiu
Application Of Integrated Geophysical Surveys In The Identification Of Hidden Fire Sources In Spontaneous Combustion Zones In Coal Seams, Ma Zijun, Yang Haiyan, Li Wenyu, Xu Yunlei, He Yunlan, Liu Zhuoming, Li Peng, Huang Jiu
Coal Geology & Exploration
Spontaneous combustion in coal seams, a factor influencing the development of many mining areas in China, can cause severe coal resource loss and environmental pollution. The positioning and distribution identification of hidden fire sources can provide an important basis for coal mine enterprises to prepare prevention and control measures. They are also a hot research topic and challenge in the field of coal fire disasters. Suitable channels for ventilation and oxygen supply are necessary for spontaneous combustion in coal seams. When the oxidative heat release rate of coals exceeds the heat dissipation rate, coal temperature will rise until the occurrence …
Change Detection Of Open-Pit Mines Based On Fm-Unet++ And Gf-2 Satellite Images, Du Shouhang, Li Wei, Xing Jianghe, Zhang Chengye, She Changchao, Wang Shaoyu, Li Jun
Change Detection Of Open-Pit Mines Based On Fm-Unet++ And Gf-2 Satellite Images, Du Shouhang, Li Wei, Xing Jianghe, Zhang Chengye, She Changchao, Wang Shaoyu, Li Jun
Coal Geology & Exploration
Automatic extraction of land use change information in open-pit mines using the remote sensing and deep learning technology is of great significance for the mining monitoring and ecological environmental protection. A novel deep learning model FM-UNet++ was constructed for the change of land use types in complex and heterogeneous mining scenarios, and the automatic change detection of open-pit mines was achieved using the Gaofen-2 (GF-2) satellite images. Firstly, the change detection dataset of open-pit mine was produced through data surveys and visual interpretation, which was augmented by data enhancement. Secondly, the FM-UNet++ for open-pit mine change detection was constructed by …
Deformation Prediction Of Open-Pit Mine Slope Based On Abc-Grnn Combined Model, Ning Yongxiang, Cui Ximin, Cui Jianguo
Deformation Prediction Of Open-Pit Mine Slope Based On Abc-Grnn Combined Model, Ning Yongxiang, Cui Ximin, Cui Jianguo
Coal Geology & Exploration
Accurate prediction of slope deformation in open-pit mine is an important guarantee for effective disaster early warning of slope. The traditional slope deformation prediction method is unable to characterize and comprehensively analyze the effect of various factors on slope deformation. In view of this, the combined prediction model (ABC-GRNN) of an artificial bee colony algorithm (ABC) and the optimized generalized regression neural network (GRNN) was proposed for slope deformation in open-pit mine. In this prediction model, the following 5 factors affecting the slope deformation of open-pit mine are considered comprehensively: mining disturbance, rainfall, rainfall duration, temperature and humidity. Herein, the …