基于GIS煤矿开采沉陷管理信息系统的设计与实现

发布时间：2018-02-28 13:01

本文关键词： ArcGIS Engine 煤矿开采沉陷概率积分法灰色理论预测模型沉陷管理信息系统　出处：《江西理工大学》2013年硕士论文　论文类型：学位论文

【摘要】：据调查，井下煤炭能源居我国矿产总资源之首，如何利用最先进的技术对其进行充分化、规模化、合理化的开采，同时又不会威胁到人类及生态环境，反而还能满足人们日益膨胀的能源消费需求，是保证煤炭行业健康、稳定、可持续发展的关键所在。然而煤炭开发与利用是一把双刃剑，我们在不断的实践、研究和尝试中都会带来或多或少的危害，大多表现在开采沉陷变形方面，这样必将导致生态破坏、物种灭绝等问题，严重者将会危及到人类生存。因此为了能使煤炭行业健康、稳定而长期的发展下去，我们有必要对开采沉陷防治工作进行研究。本文借助Visual Studio2010开发工具，基于ArcGIS Engine开发平台完成了煤矿开采沉陷管理信息系统的设计与实现。另外，本系统选用SQLServer2008数据库来完成沉陷信息数据的存储、编辑等工作；建立概率积分法预测模型，对不同形状工作面的下沉、倾斜、曲率、移动、变形等趋势进行预计，并绘制相应曲线；同时，本系统还建立了灰色理论预测模型，基于实测周期数据，对概率积分预计下沉及移动值进行预测，估算各地面点将可能在未来的哪些时刻达到概率积分预计下沉量和移动值。本文采用河南某煤矿的开采沉陷信息数据进行实验，最终完成了工作面的开采沉陷预计工作，绘制相应曲线。另外，，本系统结合21041工作面走向主断面观测线的周期观测下沉数据，建立灰色预计模型，最后估算出各测点可能会在2015年2月份至3月份左右达到概率积分预计下沉值。研究与实践结果表明，本系统不但操作简便、界面友好及计算速度快，而且还能够为实时监控、预测及预报矿山灾害发生提供一个面向对象的操作平台，方便相关煤炭管理部门和生产部门进行全局管理，并提出合理而正确的决策。
[Abstract]:According to the investigation, the underground coal energy ranks first among the total mineral resources of our country. How to utilize the most advanced technology to fully, scale and rationalize the exploitation, at the same time, it will not threaten the human beings and the ecological environment, On the contrary, it can also meet the ever-expanding energy consumption needs of people, and is the key to ensuring the healthy, stable and sustainable development of the coal industry. However, the development and utilization of coal is a double-edged sword, and we are constantly practicing. Research and attempts will bring more or less harm, most of which will be manifested in the mining subsidence deformation, which will inevitably lead to ecological destruction, species extinction and other problems, serious will endanger the survival of mankind. Therefore, in order to make the coal industry healthy, With the steady and long-term development, it is necessary for us to study the prevention and cure of mining subsidence. In this paper, the design and implementation of the coal mining subsidence management information system based on the ArcGIS Engine development platform is completed with the help of Visual Studio2010 development tools. In addition, the system selects SQLServer2008 database to complete the storage and editing of subsidence information data. The probabilistic integration method is established to predict the subsidence, inclination, curvature, movement and deformation of different working faces, and the corresponding curves are drawn. At the same time, the grey theory prediction model is established. Based on the measured period data, the predicted subsidence and movement values of probabilistic integrals are predicted. This paper uses the mining subsidence information data of a certain coal mine in Henan to carry on the experiment, and finally completes the mining subsidence prediction work of the working face. In addition, the grey prediction model is established based on the periodic observation subsidence data of the main section observation line of 21041 face. Finally, it is estimated that the predicted probabilistic integral subsidence may be reached between February 2015 and March. The results of research and practice show that the system is not only easy to operate, friendly interface and fast calculation, but also can provide an object-oriented operating platform for real-time monitoring, prediction and prediction of mine disasters. To facilitate the overall management of relevant coal management and production departments, and put forward reasonable and correct decisions.
【学位授予单位】：江西理工大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：P642.26;P208

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