The risk of rockbursts is one of the main threats in hard coal mines. Compared to other underground mines, the number of factors contributing to the rockburst at underground coal mines is much greater.Factors such as ...The risk of rockbursts is one of the main threats in hard coal mines. Compared to other underground mines, the number of factors contributing to the rockburst at underground coal mines is much greater.Factors such as the coal seam tendency to rockbursts, the thickness of the coal seam, and the stress level in the seam have to be considered, but also the entire coal seam-surrounding rock system has to be evaluated when trying to predict the rockbursts. However, in hard coal mines, there are stroke or stress-stroke rockbursts in which the fracture of a thick layer of sandstone plays an essential role in predicting rockbursts. The occurrence of rockbursts in coal mines is complex, and their prediction is even more difficult than in other mines. In recent years, the interest in machine learning algorithms for solving complex nonlinear problems has increased, which also applies to geosciences. This study attempts to use machine learning algorithms, i.e. neural network, decision tree, random forest, gradient boosting, and extreme gradient boosting(XGB), to assess the rockburst hazard of an active hard coal mine in the Upper Silesian Coal Basin. The rock mass bursting tendency index WTGthat describes the tendency of the seam-surrounding rock system to rockbursts and the anomaly of the vertical stress component were applied for this purpose. Especially, the decision tree and neural network models were proved to be effective in correctly distinguishing rockbursts from tremors, after which the excavation was not damaged. On average, these models correctly classified about 80% of the rockbursts in the testing datasets.展开更多
Laser cladding of 316 L steel powders on pick substrate of coal mining machine was conducted, and microstructure of laser cladding coating was analyzed. The micro-hardness of laser cladding coating was examined. The r...Laser cladding of 316 L steel powders on pick substrate of coal mining machine was conducted, and microstructure of laser cladding coating was analyzed. The micro-hardness of laser cladding coating was examined. The results show that microstructure of laser cladding zone is exiguous dentrite, and there are hard spots dispersible distribution in the laser cladding zone. Performances of erode-resistant, surface micro-hardness and wear-resistant are improved obviously.展开更多
Traditional coal mining and utilisation patterns are severely detrimental to natural resources and environments and significantly impede safe, low-carbon, clean, and sustainable utilisation of coal resources. Based on...Traditional coal mining and utilisation patterns are severely detrimental to natural resources and environments and significantly impede safe, low-carbon, clean, and sustainable utilisation of coal resources. Based on the idea of in situ fluidized coal mining that aims to transform solid coal into liquid or gas and transports the fluidized resources to the ground to ensure safe mining and low-carbon and clean utilisation, in this study, we report on a novel in situ unmanned automatic mining method. This includes a flexible, earthworm-like unmanned automatic mining machine (UAMM) and a coal mine layout for in situ fluidized coal mining suitable for the UAMM. The technological and economic advantages and the carbon emission reduction of the UAMM-based in situ fluidized mining in contrast to traditional mining technologies are evaluated as well. The development trends and possible challenges to this design are also discussed. It is estimated that the proposed method costs approximately 49% of traditional coal mining costs. The UAMM-based in situ fluidized mining and transformation method will reduce CO2 emissions by at least 94.9% compared to traditional coal mining and utilisation methods. The proposed approach is expected to achieve safe and environmentally friendly coal mining as well as lowcarbon and clean utilisation of coal.展开更多
基金supported by the Ministry of Science and Higher Education, Republic of Poland (Statutory Activity of the Central Mining Institute, Grant No. 11133010)
文摘The risk of rockbursts is one of the main threats in hard coal mines. Compared to other underground mines, the number of factors contributing to the rockburst at underground coal mines is much greater.Factors such as the coal seam tendency to rockbursts, the thickness of the coal seam, and the stress level in the seam have to be considered, but also the entire coal seam-surrounding rock system has to be evaluated when trying to predict the rockbursts. However, in hard coal mines, there are stroke or stress-stroke rockbursts in which the fracture of a thick layer of sandstone plays an essential role in predicting rockbursts. The occurrence of rockbursts in coal mines is complex, and their prediction is even more difficult than in other mines. In recent years, the interest in machine learning algorithms for solving complex nonlinear problems has increased, which also applies to geosciences. This study attempts to use machine learning algorithms, i.e. neural network, decision tree, random forest, gradient boosting, and extreme gradient boosting(XGB), to assess the rockburst hazard of an active hard coal mine in the Upper Silesian Coal Basin. The rock mass bursting tendency index WTGthat describes the tendency of the seam-surrounding rock system to rockbursts and the anomaly of the vertical stress component were applied for this purpose. Especially, the decision tree and neural network models were proved to be effective in correctly distinguishing rockbursts from tremors, after which the excavation was not damaged. On average, these models correctly classified about 80% of the rockbursts in the testing datasets.
文摘Laser cladding of 316 L steel powders on pick substrate of coal mining machine was conducted, and microstructure of laser cladding coating was analyzed. The micro-hardness of laser cladding coating was examined. The results show that microstructure of laser cladding zone is exiguous dentrite, and there are hard spots dispersible distribution in the laser cladding zone. Performances of erode-resistant, surface micro-hardness and wear-resistant are improved obviously.
基金The authors gratefully acknowledge the financial support provided by the State Key Research Development Program of China (Grant Number 2016YFC0600705)the National Natural Science Foundation of China (Grant Numbers 51674251, 51727807, and 51374213)+1 种基金the National Major Project for Science and Technology (Grant Number 2017ZX05049003-006)and the Innovation Teams of Ten-thousand Talents Program sponsored by the Ministry of Science and Technology of China (Grant Number 2016RA4067).
文摘Traditional coal mining and utilisation patterns are severely detrimental to natural resources and environments and significantly impede safe, low-carbon, clean, and sustainable utilisation of coal resources. Based on the idea of in situ fluidized coal mining that aims to transform solid coal into liquid or gas and transports the fluidized resources to the ground to ensure safe mining and low-carbon and clean utilisation, in this study, we report on a novel in situ unmanned automatic mining method. This includes a flexible, earthworm-like unmanned automatic mining machine (UAMM) and a coal mine layout for in situ fluidized coal mining suitable for the UAMM. The technological and economic advantages and the carbon emission reduction of the UAMM-based in situ fluidized mining in contrast to traditional mining technologies are evaluated as well. The development trends and possible challenges to this design are also discussed. It is estimated that the proposed method costs approximately 49% of traditional coal mining costs. The UAMM-based in situ fluidized mining and transformation method will reduce CO2 emissions by at least 94.9% compared to traditional coal mining and utilisation methods. The proposed approach is expected to achieve safe and environmentally friendly coal mining as well as lowcarbon and clean utilisation of coal.
