煤矿安全目标检测技术研究进展
王新航
（华北科技学院，河北 廊坊 065201）
摘要： 信息化时代的发展使得煤炭行业向智能化、智慧化转型升级。为了确保煤矿生产安全运行，坚持“以人为本”
的发展理念，煤矿安全目标检测技术的研究发展成为数字化矿山安全建设不可或缺的一步。介绍了传统目标检测算法、
基于区域建议和分类回归的深度学习算法等的研究进展以及在井下应用的优缺点，重点分析不同算法的作用机理及特
点，最后结合目前存在的问题探讨了煤矿安全目标检测未来可能的发展趋势。
关键词： 煤矿安全；目标检测；深度学习
中图分类号： TP391.41      文献标志码： A      文章编号： 2095-0802-(2023)04-0118-03
Research Progress of Coal Mine Safety Target Detection Technology
WANG Xinhang
(North China Institute of Science and Technology, Langfang 065201, Hebei, China)
Abstract: The development of the information age has made the coal industry transform and upgrade to intelligence and
intelligence. In order to ensure the safe operation of coal mine production and adhere to the development concept of "peopleoriented",
the research and development of coal mine safety target detection technology has become an indispensable step in the
safety construction of digital mines. This paper introduced the research progress of traditional target detection algorithm, deep
learning algorithm based on region recommendation and classification regression, as well as the advantages and disadvantages of
underground application, emphatically analyzed the mechanism and characteristics of different algorithms. Finally, it discussed the
possible future development trend of coal mine safety target detection based on the existing problems.

Key words: coal mine safety; target detection; deep learning