摘要
为提高工作面煤与瓦斯突出预警系统的预警准确率及智能化程度,以山西省吕梁市某矿11301掘进工作面为研究背景,引入人工智能大数据挖掘算法构建基于FOA-RF的煤与瓦斯突出危险性智能预测模型,利用微震及红外甲烷传感器实时监测工作面煤与瓦斯突出危险状态,设计开发了煤与瓦斯突出智能预警系统,并将该系统应用至11301掘进工作面的突出危险性预警中。应用结果显示,智能预测模型的训练精度为99.59%,预测精度为94.57%,所建预警系统能较好地对实时预警指标数据进行可视化分析及管理,预警结果与工作面实际突出状态基本一致。
To improve the coal and gas outburst early warning accuracy and intelligent degree of working face,taking the 11301 tunneling working face of a mine in Lvliang city,Shanxi province as the research background,an intelligent coal and gas outburst prediction model using big data mining algorithm is built based on FOA-RF.The coal and gas outburst dangerous state of working face is real-time monitored using seismic and infrared methane sensor.The intelligent warning system of coal and gas outburst is designed and developed,which is applied to 11301 tunneling working surface for outburst dangerous warning.The application results show that:the training accuracy of the intelligent prediction model is 99.59%,and the prediction accuracy is 94.57%.The established early warning system can perform the visual analysis and management of real-time warning index data,and the early warning results are basically consistent with the actual outburst state of the working face.
作者
张清清
ZHANG Qingqing(CCTEG Shenyang Research Institute Co.,Ltd.,Fushun 113122,China;National Key Lab of Coal Safety Technology,Fushun 113122,China)
出处
《陕西煤炭》
2024年第7期152-155,161,共5页
Shaanxi Coal
关键词
随机森林算法
果蝇算法
煤与瓦斯突出
智能预警系统
random forest algorithm
fruit flies algorithm
coal and gas outburst
intelligent early warning system
