一种煤矿瓦斯智能化监测系统及其优化研究  

Optimization of intelligent monitoring system for a coal mine gas

作　　者：史沁彬 弓伟 SHI Qinbin;GONG Wei(Changcun Coal Mine,Shanxi Lu’an Environmental Energy Co.,Ltd.,Changzhi 046102,China;Key Laboratory of In-Situ Property-Improving Mining of Ministry of Education,Taiyuan University of Technology,Taiyuan 030024,China)

机构地区：[1]山西潞安环能股份有限公司常村煤矿,山西长治046102 [2]太原理工大学原位改性采矿教育部重点实验室,山西太原030024

出　　处：《陕西煤炭》2024年第12期164-167,共4页Shaanxi Coal

摘　　要：智能化监测技术为瓦斯的安全防治提供了有力保障,是煤矿智能化建设的重要组成部分。通过对保德煤矿瓦斯智能化监测系统技术组成与特点的总结,探讨了保德煤矿瓦斯智能化监测系统目前存在的局限性,并阐述了引入DBN深度学习算法用于瓦斯浓度的监测与预警的改进措施。结果表明,DBN学习算法在瓦斯浓度状态识别方面具有良好的准确度,可为煤矿瓦斯智能化监测工作提供参考。Intelligent monitoring technology provides a strong guarantee for gas prevention and control,and is an important part of intelligent construction in coal mines.Based on the summary of the technical composition and characteristics of the intelligent gas monitoring system in Baode Coal Mine,we discuss the current limitations of the system,and elaborate on the improvement measures for the monitoring and early warning of gas concentration by introducing the DBN deep learning algorithm.The results show that the DBN learning algorithm has good accuracy in gas concentration state identification and can provide reference for intelligent gas monitoring in coal mines.

关 键 词：煤矿智能化 瓦斯浓度智能化监测 DBN 浓度阈值差异化 

分 类 号：TD76[矿业工程—矿井通风与安全]