Variance Analysis in China’s Coal Mine Accident Studies Based on Data Mining

Abstract

The risk of coal mine accidents rises significantly with mining depth, making it urgent for accident prevention to be supported by both scientific analysis and advanced technologies. Hence, a comprehensive grasp of the research progress and differences in hotspots of coal mine accidents in China serves as a guide to find the shortcomings of studies in the field, promote the effectiveness of coal mine disaster management, and enhance the prevention and control ability of coal mine accidents. This paper analyzes Chinese and foreign literature based on data mining algorithms (LSI + Apriori), and the findings indicate that: (1) 99% of the available achievements are published in Chinese or English-language journals, with the research history conforming to the stage of Chinese coal industry development, which is characterized by “statistical description, risk evaluation, mechanism research, and intelligent reasoning”. (2) Chinese authors are the primary contributors that lead and contribute to the continued development of coal mine accident research in China globally. Over 81% of the authors and over 60% of the new authors annually are from China. (3) The emphasis of the Chinese and English studies is different. Specifically, the Chinese studies focus on the analysis of accident patterns and causes at the macroscale, while the English studies concentrate on the occupational injuries of miners at the small-scale and the mechanism of typical coal mine disasters (gas and coal spontaneous combustion). (4) The research process in Chinese is generally later than that in English due to the joint influence of the target audience, industrial policy, and scientific research evaluation system. After 2018, the Chinese studies focus significantly on AI technology in deep mining regarding accident rules, regional variation analysis, risk monitoring and early warning, as well as knowledge intelligence services, while the hotspots of English studies remain unchanged. Furthermore, both Chinese and English studies around 2019 focus on “public opinion”, with Chinese ones focusing on serving the government to guide the correct direction of public opinion while English studies focus on critical research of news authenticity and China’s safety strategy.

Study of a Small Robot for Mine Hole Detection

“…China is rich in coal resources, but the complex geological conditions of coal mines and the difficulties in mining have led to frequent coal mine production accidents in China, and there is a significant gap in the safety situation of coal mines compared with that of developed countries [1][2][3][4][5][6]. According to relevant statistics, between 2008 and 2021, the total number of coal mine accidents in China reached 1157, causing a large number of casualties and property losses, of which roof accidents and water damage accounted for 44.43%, resulting in 514 deaths; this represents a severe hazard [7,8]. These accidents are closely related to local hydrogeological conditions, and the use of mine hole-detection technology can determine the stratigraphic conditions of coal mines, which can effectively reduce the risk of coal mining.…”