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Study And Software Development Of Ground Movement And Deformation In Mining Area

Posted on:2009-09-08Degree:MasterType:Thesis
Country:ChinaCandidate:J DengFull Text:PDF
GTID:2121360272963944Subject:Geodesy and Survey Engineering
Abstract/Summary:PDF Full Text Request
Mining subsidence prediction is one of the core contents in mining subsidence subject. With the prediction results, we can quantitatively research on the distribution law of strata and ground movement effected by the mining in time and space. It is important to guide the mining practice, which are under buildings, railways and water. The ground movement and deformation prediction mainly includes: the prediction after mining and ground subsidence basin is stable and dynamic prediction during mining. This thesis is major in the movement and deformation prediction with probability integral method after ground subsidence basin is stable and dynamic prediction ofsurface subsidence through building the model of Kalman filtering during mining.The probability integral method is very important in mining subsidence prediction in our country. On the basis of studying the theory, this thesis implements movement and deformation prediction in the main profile of ground subsidence basin and generates two-dimensional visual graphics. At the same time it implements the computerization of movement and deformation prediction of any points and generates the three-dimension visual graphics with ArcGIS.Kalman filtering is a effective method of data processing in dynamic system. This paper uses it to predict the movement and deformation during mining. With building the model of Kalman filtering we can filter and estimate observation data and then dynamic predict the situation of surface move observation station. As the movement and deformation is a complex and dynamic changing process this paper uses two algorithms included standard Kalman filtering and adaptive Kalman filtering After analysis and comparison, adaptive Kalman filtering as an improved algorithm is better than standard Kalman filtering in filtering. In dynamic prediction, however, when the observation station has little influence or changes slowly the prediction result is good while it has large deviation as sudden change of state. This needs further study and exploration.In the above ground movement and deformation prediction the paper has analyzed and compared the prediction value with measured value with examples. With programming tool of object-oriented language VB6.0 and combining with AutoCAD2004 we develop the software -The system of ground movement and deformation prediction.
Keywords/Search Tags:Ground movement and deformation prediction, Probability integral method, Kalman filtering, Adaptive Kalman filtering, Prediction
PDF Full Text Request
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