摘要
为推进我国煤与瓦斯突出预测预警技术发展,对预测指标和预警方法的研究现状进行了分析。在预测指标方面,目前我国采用较多的是煤的破坏类型、瓦斯放散指数Δp、煤体坚固性系数f、瓦斯压力p、钻屑综合指标、钻孔瓦斯涌出初速度q、R值等静态指标;近年来,电磁辐射、声发射、微震监测等可被连续检测的动态预测指标均得到了较好应用,采用的综合指标瓦斯膨胀能也有较高的可靠性。在预测预警方法方面,灰色理论和神经网络等理论和方法在煤与瓦斯突出的预测预警中取得了一定的成果。分析发现,目前的预测指标与方法都存在一定的缺陷,而物理模拟试验和室内试验相结合的研究方法必然是以后的发展趋势。
In order to promote the development of China’s coal and gas outburst prediction and early warning technology,the research status of forecasting indicators and forecasting methods were analyzed.In the aspect of prediction indexes,the static indexes such as coal failure type,gas dissipation index,coal firmness coefficient,gas pressure,drilling cuttings comprehensive indexes,drilling gas gushing initial velocity and R value were widely used in China.In recent years,the dynamic prediction indexes such as electromagnetic radiation,acoustic emission and microseismic monitoring that can be continuously detected have been well applied,and the comprehensive index gas expansion energy adopted has high reliability.In the aspect of prediction and early warning methods,the application of grey theory and neural network has made some achievements.The analysis shows that there are some defects in the current prediction indexes and methods,and the research method combining physical simulation test and indoor test will be the future development trend.
作者
韩云春
任波
杨理强
陈本良
段昌瑞
邓东生
李志兵
HAN Yun-chun;REN Bo;YANG Li-qiang;CHEN Ben-liang;DUAN Chang-rui;DENG Dong-sheng;LI Zhi-bing(Ping’an Coal Mining Engineering Technology Research Institute Co.,Ltd.,Huainan 232000,China;School of Resources and Safety Engineering,China University of Mining and Technology(Beijing),Beijing100083,China;State Key Laboratory of Deep Coal Mining and Environmental Protection,Huainan 232000,China;School of Energy and Safety,Anhui University of Science and Technology,Huainan 232001,China)
出处
《陕西煤炭》
2020年第1期51-53,12,共4页
Shaanxi Coal
基金
国家重点研发计划项目(2018YFC0808000)
面向井下钻孔机器人施工的瓦斯防治钻孔智能设计技术
关键词
煤与瓦斯突出
预测指标
预警方法
研究现状
发展趋势
coal and gas outburst
forecast indicators
early warning methods
research status
development trend
