Analysis of the Current Status and Hot Technologies of Coal Spontaneous Combustion Warning

被引:6
|
作者
Wang, Feiran [1 ]
Ji, Zhansuo [2 ]
Wang, Haiyan [3 ]
Chen, Yue [1 ]
Wang, Tao [3 ]
Tao, Ruoyi [1 ]
Su, Chang [1 ]
Niu, Guchen [1 ]
机构
[1] China Univ Min & Technol Beijing, Sch Emergency Management & Safety Engn, Beijing 100083, Peoples R China
[2] Qianjiaying Min Branch Co, Kailuan Grp Co Ltd, Tangshan 063000, Peoples R China
[3] Univ Sci & Technol Beijing, Sch Civil & Resources Engn, Beijing 100083, Peoples R China
基金
中国国家自然科学基金;
关键词
coal spontaneous combustion warning; marker gas; warning model; VOSviewer; LONGWALL GOB; INDEX GASES; PREDICTION; IGNITION;
D O I
10.3390/pr11082480
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Coal spontaneous combustion disasters are one of the most serious types of mine disasters in China at present, posing a huge threat to underground personal safety and coal production operations. In order to prevent and control coal spontaneous combustion hazards and construct an efficient early warning system, this paper presents a review of coal spontaneous combustion early warning based on the Web of Science database search of 583 papers related to coal spontaneous combustion early warning collected from 2002 to 2021, using VOSviewer visualization software. The number of publications and partnerships at the author, institution and country levels are obtained, and the research hotspots in the field of coal spontaneous combustion warning are obtained based on keyword co-occurrence and clustering. The results show that the research results of scholars with a high publication volume have significant influence in the field of coal spontaneous combustion warning and prevention and control, and a more mature camp has been formed among the research authors; a more stable core group of institutions has been formed in the field of coal spontaneous combustion warning; most of the national publications are concentrated in mineral resource-mining countries; the analysis of hot keywords shows that "sign gas warning" and "warning models and technologies" are the key contents of this field. The analysis of hot keywords shows that "sign gas early warning" and "early warning model and technology" are the key contents of this field. The research content of this paper is helpful for researchers to find the latest information on the current research and trends in the field of spontaneous combustion prevention and coal seam monitoring.
引用
收藏
页数:17
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