The Dynamic Monitoring Of Mine High Slope And Its Stability Prediction

With the ongoing mining more and more open pit into the furrow mining phase thatmakes the stability of high and steep slope get worse. In addition, mining enterprises cannot really grasp the law of development and deformation of slope. Because of high andsteep slope is lacking of scientific and reasonable means of monitoring in a long time bymining enterprises that lay hidden to mine production safety. Therefore, more and morerequires a wide range, regular and continuous method to get deformation parameters ofmine slope, and treatment parameters timely and effective. Then make a scientificanalysis and prediction to slope stability.Deformation of slope is a development processing from the micro to the macro. Theonly way to get the tiny deformation and development law of target point is the use ofprecision instruments and strict monitoring methods. Georobot achieved the automaticmeasurement to target point, which Integration of motor and CCD image sensor andusing ATR (Automatic Target Recognition) automatic target recognition technology.Meanwhile, Leica Geo systems company provide the application development platform"GeoBasic" and the Interface technology platform "GeoCOM" which based on computeronline control technology to their own production Georobot. Users can develop programswhich uploaded to the instrument as their required, they can also develop applications onthe external device.In the research work of slope deformation monitoring, monitoring is the means andprediction is the goal. After years of research, analysis and processing to deformationdata has formed a mature theoretical system now, and people established a wealth oftrend fitting and forecasting model, such as regression analysis model, Kalman filtermodel, time series model, wavelet theory, gray model and artificial neural networkmodels, etc.Shi Rengou iron ore is one of the oldest iron ore mines that is from open pit tounderground in our country. This paper has the Shi Rengou iron slope deformationmonitoring system for the study, using of Regression model and wavelet transformremove the raw data’s noise, restoring the true value of the deformation. Then it creates agray prediction GM (1,1) model to predict the deformation trend of the slope. Throughcomparative analysis of horizontal and vertical, proves the effects of precision of grayforecasting model by data sequences with different lengths. Also it verifies that thecombination of gray theory and wavelet transform can effectively improve the predictionof the accuracy of the model.