【作者】 魏红霞；

【导师】 张英梅；

【作者基本信息】 太原理工大学 ， 测试计量技术及仪器， 2010， 硕士

【摘要】 煤炭行业是诸多能源行业当中的高危行业,其开采一直受到很多条件的限制,其中地下水是威胁煤矿安全生产的重要因素之一。最近,多起重大、特大煤矿突水事件屡见报端,主要是因为煤矿突水形成十分复杂,涉及到水文、地质构造、采动影响等方面的要素,而目前又缺乏在采掘过程中的实时动态监测,因此给人民的生命财产造成了极大的危害。针对煤矿开采过程中缺乏有效的动态监测手段、预测方法单一等缺点,研究神经网络和D-S证据理论相结合的两级融合算法,提出了煤矿井下多参数突水信息的动态评价方法。此方法将传感器技术、数据融合技术和自动控制技术相结合,实现了煤矿井下传感器数据的动态采集、实时传输及突水等级的确定,为预防水害的发生提供决策依据。目前关于突水的数据还很少,而突水预测需要大量的数据。因此,提出了在采掘工作面区域内进行分布式多方位传感器布置的方案。首先确定影响工作面突水的诸多因素,通过分析煤矿顶板、底板突水机理,得出影响突水的主要因素,如巷道导水沟水位、含水层水位、顶、底板压力和掘进面前方的水量等。其次,选取了山西省漳村、沙坪两个煤矿进行实例分析,根据两个煤矿不同的水文、地质结构条件,对应的进行了传感器的布置,从而进行水情动态多参数测量。提出了建立井下现场动态水情数据库,填补了煤矿井下动态水情信息数据的空白。系统以VC++作为软件开发平台,Microsoft SQL Server为数据库平台,采用类三层C/S结构的开发模式,结合以太网标准PROFINET通讯技术,实现对煤矿井下的压力、水位、温度、流量等数据的实时传输,将采集到的数据预处理、传输到井下变电所的防爆PC机整理、分类、存储。然后,将采集到的数据进一步分析,应用两级融合算法,计算得出关于煤矿井下工作面突水的安全等级状态。对山西漳村煤矿3#煤层进行了实例分析,从开采、探测资料中提取10组已采点作为构建预测模型的样本,运用两级融合算法对煤矿井下突水等级评估。结果表明,该两级融合算法能够准确评估出煤矿井下突水的程度,有较强的抗干扰能力和较高的准确度,从而验证了系统的有效性和可行性。更多还原

【Abstract】 The coal industry is one of the most dangerous energy industries, its exploitation has been subjected to many conditions, the threat of groundwater which is an important factor in coal mine production safety. Recently, several important, large water inrush events are often found in newspapers. The water inrush of coal mines causes by some complex elements, involving hydrology, geology, mining effect etc.. At present, it is short of real-time dynamic monitoring in the excavating process, which jeopardized to people’s lives and wealth.According to the problems of the lack of real-time monitoring and single detection method during the excavating process, combined with neural network and the D-S evidence theory fusion algorithm, it is proposed that the predictive method of coal mining water inrush based on multi-parameter is studied. This method is the integration of sensing technology, data fusion technology and automation technology. It achieves the aim of the mine sensor data collection in time, real-time transmission and determination of the water inrush level ,to provide the basis for preventing water damage. At present,the datas about water inrush are still short, while large amounts of datas are required in water inrush prediction. The method is proposed that distributed multi-directional sensors are arranged in the mining working face. Firstly,many factors affecting workface inrush are determined.Through analysis of the mechanism of coal top and bottom board inrush, the main factors are obtained,such as roadway gutter water level, aquifer water level, top, bottom board pressure and the amount of water before driving side and so on.Secondly, the ShaPing and ZhangCun coal in Shanxi Province are analyzed, according to two different hydrological, geological structure conditions, correspondingly arranging the sensors to measure the dynamic parameter.The dynamic water regimen database is established, filling the blank of the dynamic hydrologic data. The system takes VC++ as a software development platform and choose Microsoft SQL Server as the database system,adopting structure of C/S as development model,combing with the Ethernet standard PROFINET Communication technology. It realizes the real-time data transimission about the pressure on the coal mine,water level,temperature,flow.Then the collected datas are pretreated and transmitted to the underground substation flameproof computer putting into the database. At the same time, the collected datas are analyzed further, using the fusion algorithm, and finally the safety level about coal water inrush is reached.It is made a case study which used the data of 3 # coal in ZhangCun of Shanxi Province,10 points has been taken as the group sample for building prediction model from the mining and exploration data.And the fusion algorithm is used to evaluate water inrush level in mining.The results show that the fusion algorithm can accurately assess the situation of underground mine water inrush ,it has anti-jamming capability and high accuracy and it’s proofed that the system is effective and feasible.更多还原