Applied Research Of Kriging Interpolation Method In Distributed Detection Of Coal Seam

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.