摘要
为解决矿井顶板灾变预报预警的难题,综合运用理论分析、力学建模、数值分析和工程实践等多种方法,分析了采场顶板的灾变形式和力学机理;基于多因素径向基神经网络数学模型设计出矿井顶板灾害预警系统软件,可对采场顶板岩层下沉量和致灾程度进行预判,并通过了现场实践验证,有效预防了矿山顶板灾害的发生。
In order to solve the problem of prediction and early warning about mine roof disasters, the methods of theoretical analysis, mechanical modeling, numerical analysis and engineering practice are comprehensively applied to analyze the roof disaster forms and mechanical mechanism of the stope. We designed the software of roof disaster early warning system which is based on multi-factor radial basis neural network mathematical model, and then prejudged the settlement of the roof rock of the stope and the degree of the disaster. The system has effectively prevented the mine roof disaster through the field practice verification.
作者
秦兵文
谢福星
QIN Bingwen;XIE Fuxing(Inner Mongolia Baoshan Baoma Mining Co., Ltd., Xilinhot 026000,China;1nstitute of Mine Construction, Tiandi Science ＆ Technology＂ Co., Ltd., Beijing 100013, China;Beijing China Coal Mine Engineering Co., Ltd., Beijing 100013, China)
出处
《煤矿安全》
CAS
北大核心
2018年第5期124-127,共4页
Safety in Coal Mines
基金
国家自然科学基金资助项目(51604114)
关键词
采场顶板
力学建模
数值分析
神经网络
预警系统
stope roof
mechanical modeling
numerical analysis
neural network
early warning
