Qiao Wanguan, Chen Xue
School of Economics and Management, Jiangsu Vocational Institute of Architectural Technology, Xuzhou, 221116, China.
School of General Course, Jiangsu Vocational Institute of Architectural Technology, Xuzhou, 221116, China.
Heliyon. 2022 Nov 23;8(11):e11834. doi: 10.1016/j.heliyon.2022.e11834. eCollection 2022 Nov.
With the continuous development of automation and information technology, large amounts of safety data are produced in the processes of coal production. Most enterprises simply focus on statistics and do not conduct systematic big data analyses. Therefore, it is necessary to study the theory of coal mine safety while using big data systematically. This paper expounds on the changes in coal mine safety that have been driven by big data from three aspects: the connotation, characteristics and research framework. First, the connotation of coal mine safety big data (CMSBD) is redefined by changing the safety entities and methods. Second, the advantages and disadvantages of the big data model are compared from the perspective of feature analysis. Finally, the research paradigm and technical framework of CMSBD are designed. The results show that the management connotation of CMSBD focuses on the role of big data in coal mine safety. Compared with coal mine safety small data (CMSSD), CMSBD has both advantages and disadvantages. Therefore, CMSBD must be combined with a small data method. The research paradigm emphasizes the intersection of the research, the relevance of safety thinking, the importance of safety data analysis, and the fusion of big data with traditional small data models.
随着自动化和信息技术的不断发展，煤炭生产过程中产生了大量安全数据。大多数企业仅仅注重统计，并未进行系统的大数据分析。因此，有必要在系统运用大数据的同时研究煤矿安全理论。本文从内涵、特征和研究框架三个方面阐述了大数据驱动下的煤矿安全变化。首先，通过改变安全实体和方法重新定义了煤矿安全大数据（CMSBD）的内涵。其次，从特征分析的角度比较了大数据模型的优缺点。最后，设计了CMSBD的研究范式和技术框架。结果表明，CMSBD的管理内涵侧重于大数据在煤矿安全中的作用。与煤矿安全小数据（CMSSD）相比，CMSBD既有优势也有劣势。因此，CMSBD必须与小数据方法相结合。研究范式强调研究的交叉性、安全思维的相关性、安全数据分析的重要性以及大数据与传统小数据模型的融合。
