摘要
针对当前矿山顶板灾害监测预警系统预警的有效性和精确性不足等问题,提出了基于人工神经网络的多因素径向基神经网络数学模型,对矿山压力显现状态、顶板岩层结构状态及顶板下沉量等监测模块进行了优化设计,加入了决策响应板块,形成了综合性矿山顶板灾害监测预警系统,并对8707工作面进行工业性应用监测。结果表明,8707工作面顶板结构处于滑落回转阶段,应加强对8707工作面倒架、压架等矿压显现异常现象的防范工作。
In view of the insufficient availability and accuracy of the roof disaster monitoring and early warning system in mines at present,the paper proposed a multi-factor radial basis neural network mathematical model based on artificial neural network,and optimized the modules such as monitoring the strata behavior,roof rock status and roof subsidence amount etc.After that,the decision-making section was added to form a comprehensive mine roof disaster monitoring and early warning system,and then the system was put into the industrial monitoring for work face 8707.The results showed the roof on work face 8707 was in the sliding and turning stage,it was necessary to strengthen the preventation duty for the support overturning and pressing on work face 8707.
作者
郎琦
LANG Qi(China Coal Research Institute,Beijing 100013,China;State Key Laboratory of High Efficient Mining&Clean Utilization of Coal Resources,Beijing 100013,China;Beijing Colliery Safety Engineering Technology Research Center,Beijing 100013,China)
出处
《矿山机械》
2020年第12期16-22,共7页
Mining & Processing Equipment
基金
煤炭科学技术研究院有限公司技术创新基金Ⅰ类:煤矿采场三维应力监测装备与动态预警模型研究(2020CX-Ⅰ-08)
煤炭科学技术研究院有限公司技术创新基金:基于事件溯源的隐患排查系统研究(2019CX-Ⅱ-17)。
关键词
顶板监测
数学模型
径向基神经网络
优化设计
预警系统
roof monitoring
mathematical model
radial basis neural network
optimization design
early warning system
