【作者】 翟进乾；

【导师】 张英梅；

【作者基本信息】 太原理工大学 ， 检测技术与自动化装置， 2008， 硕士

【摘要】 本文是在山西省自然科学基金项目《多源信息融合技术在煤矿水害预测中的研究》资助下完成的,目的是对煤层分布检测方法进行应用研究。煤矿工程人员要对合理开采煤层做出决策,必须对煤层的分布有一个直观的了解,这就需要知道煤层的分布状态。对地下煤层了解的唯一途径是进行钻探检测,但进行钻探检测要花费很大的代价,所以不可能大规模的钻探。如何根据有限的钻孔检测资料来得到煤层的分布模型,本论文提出了克里金插值方法来解决钻孔数据严重不足的问题。在论文中,根据空间插值方法的基本原理,对主要的空间插值方法进行了比较,分析了各种方法的适用条件、算法和优缺点。在煤层分布检测中,克里金插值方法不仅考虑了观测点和被估计点的相对位置而且还考虑了各观测点之间的相对位置关系,并且,克里金建模具有无偏、最优的性质,点稀少时插值效果比其他方法好,能给出待估点属性值数学期望最好的近似。文中在确定插值邻域的基础上,利用克里金插值方法的多种模型对研究区散乱数据点的变异函数进行拟合。为了确定哪个插值模型更适合研究区域的三维建模,对多个插值效果图进行了比较,得出普通克里金插值方法的球状模型是最佳的插值模型。主要内容有:(1)介绍了常用空间插值方法的原理、研究现状、应用领域。分析对比每种方法的优缺点,明确了在煤层分布模型检测方面,克里金插值方法的插值效果较好。(2)根据空间信息统计学的基本原理,详细说明了变异函数的理论模型和实验模型,改进了变异函数参数的确定方法。(3)详尽阐述了克里金插值方法的基本原理,分析比较了各种克里金插值方法的优缺点及其应用条件。提出了在研究区域内采用普通克里金插值方法进行数据插值。(4)对原始采样数据进行了处理,根据改进后的参数确定方法计算出实验变异函数的参数,绘出了实验变异函数分布图,并用理论模型中的三种模型对实验变异模型进行了拟合,并对拟合的结果进行了检验,指出球状模型的效果最好。(5)采用普通克里金插值方法进行插值,根据输出结果,用Matlab软件对研究区域的煤层进行了三维模拟。(6)对建立的煤层模型进行分析应用,指出这种方法还可以应用到更多的领域。更多还原

【Abstract】 This article is sponsored by natural science fund project of Shanxi province, which is "Research of Multi-sources Information Fusion Technique In Water Invasion Prediction of Coal Seam". The aim is to carry on applied research to distributed detection method of coal seam.The project personnel of coal mine want to make decision to reasonable coal mining, they must have an intuitive understanding to coal seam’s distribution, and need to know distributed situation of coal seam. The only way is to drill hole, but it is very expensive, therefore it is impossible to drill large-scale holes. According to the limited drill holes, how to obtain the coal seam’s distribution model, this paper proposed kriging interpolation method to solve the problem which is lack of the drill holes data.In this article, according to the basic principle of spatial interpolation, several important spatial interpolation methods are compared with each other. Their application addition, algorithm, merits and shortcomings are analyzed. During distributed detection of coal seam, kriging not only considers the relative position of the observation points to the estimated points, but also the relative position of the observation points with each other, and kriging has property of unbias and minimum variance. Compared with other methods, the result of kriging interpolation is better especially in few observation points and its result is the best approximation of mathematical expectation. In this article, we determine interpolation neighborhood, fit variogram function of scattered data using many kinds of models of kriging interpolation in research area. In order to determine that which interpolation model is more suitable to three dimensional modeling in research area, several interpolation effect charts are compared, the result is that spherical model of ordinary kriging interpolation method is the best interpolation model. The main research works are as follows:1, Introduced the basic principle, the research present situation, the application domain of common spatial interpolation. Compared merits with shortcomings of each interpolation method. Pointed out the interpolation effect of kriging interpolation method is better in distributed detection of coal seam.2, According to the basic principle of spatial information statistics, introduce the theoretical model and the experimental model of variogram in detail, improve seeking method of parameter of variogram.3, Elaborate the basic principle of kriging interpolation, contrast the merits and shortcomings, the application condition of each kriging interpolation method, point out that we should use ordinary interpolation method to carry on data interpolation in research area.4, Process the original sampling data, and compute the parameters of the experimental variogram function according to improved seeking method of parameter. Draw the experimental semivariogram, fit the experimental semivariogram function with three models of the theoretical model, test the fitting result, point that the spherical model is better.5, Use ordinary kriging interpolation method to carry on data interpolation. According to the output result, simulate the coal seam with Matlab.6, Carry on the analysis application to the establishment model of coal seam, point out that this method may also apply more domains.更多还原