基于CMS实测的采空区危险度分析及其处理

【作者】 杨彪；

【导师】 罗周全；

【作者基本信息】 中南大学 ， 地下空间资源科学与工程， 2008， 硕士

【摘要】 采空区是地下资源安全开采面临的最主要灾源之一。本文综合运用现场实验、数值模拟、人工神经网络等方法,采用空区精密探测系统（CMS）和Surpac、Flac^3D、Phase²、Matlab等数字化软件工具,紧密结合“铜坑矿采区空区形态三维精密探测及数字模拟与监测技术研究”科研课题,针对铜坑矿的具体工程实际,开展基于CMS精密探测的采空区危险度分析研究,主要研究内容如下:1.以先进的空区三维激光探测系统为手段,综合运用QVOL、Surpac等软件工具,完成对采空区的现场精密探测并建立其三维空间模型,准确掌握采空区的三维形态、空间位置、实际边界、顶板面积及体积大小等信息,实现对采空区相关信息的准确有效获取;2.运用数值分析软件Flac^3D和Phase²,从位移、应力、塑性变形等方面对空区危险度进行量化分析,并以此为基础,综合考虑采空区的三维形态、空间分布以及规模大小等因素对采空区进行危险度分级;3.以采空区实测信息为基础,综合考虑空区周边矿岩物理力学性质,运用人工神经网络理论,建立采空区危险度辨识的BP神经网络模型,实现对矿山空区危险度的有效辨识;4.在上述研究的基础上,综合考虑空区周边环境、三维形态、空间位置及其与周边工程之间的关系等因素,研究提出对铜坑矿采空区进行合理处理的技术方案。研究以金属地下矿山采空区为对象,以形成金属矿山采空区精密探测、危险度分析和有效治理一体化综合技术为目标,在准确获取空区相关信息的基础上进行可靠的危险度分析,有效的进行预防由采空区引发的灾害,为安全生产提供技术指导与支持,对防止和控制矿山重、特大事故发生起到关键作用,具有重要的理论与现实意义。更多还原

【Abstract】 Goaf is one of the main hazard sources faced by underground resource mining. The paper uses the methods of field experimentation, mining and numerical simulation software, artificial neural nets, employs kinds of digitized software tool ,such as Cavity Monitoring System (CMS), Surpac, Flac Phase and Matlab, tightly couples with the scientific research of "The study of the cavity modality Three-dimensional exact explore and numerical simulation and monitoring technology in Tongkengmine", and carries on the investigation into cavity Danger degree analysis based on CMS according to the actual conditions of Tongkengmine. The main study contents are as follows:Taking the advanced Three-dimensional Cavity Monitoring System as means, integratedly using software tools such as QVOL,Surpac, finishing precise exploration of cavities and building a three-dimensional visual model exactly, mastering the information about the three-dimensional configuration, spatial position, actual border, roof area, volume of the cavities, acquiring relevant information about the cavities effectively.Quantitatively analyzing the cavity risk from the aspects of displacement, stress and plastic deformation ,by the numerical analogue analysis software-FLAC and Phase. On the basis of the above analysis, by considering the three-dimensional configuration ,space distribution and the size of cavity, the author classify its risk level.Based on the actual exploration information about the cavity, by considering the physical mechanics property of surrounding rock and making use of artificial nerve network theories, we build a BP nerve network model for predicting cavity risk, which helps to realize the valid estimate about nine cavity risk.On the basis of above research, and considering its environment , three- dimensional configuration, spatial position and its relation with surrounding project, etc., the research proposes a technical proposal for the rational dispose of Tongkeng mineing Cavity.The object of the study is metal underground mine, and aims at forming an integrated technology of accurate exploration,Danger degree analysis and effective management about the metal mine cavity. On the basis of accurate information of cavity, the author carries on reliable safety analysis,which effectively prevents the occurrence of cavity hazard. The study provides technique guidance and support for the safety production, plays a key role in preventing and controlling major and extraordinarily big accidents, and has important theoretical and realistic meaning.更多还原