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Study On Application Of InSAR Technology In Deformation Monitoring Of Hancheng Mining Area

Posted on:2020-11-19Degree:MasterType:Thesis
Country:ChinaCandidate:X MengFull Text:PDF
GTID:2381330590459440Subject:Geodesy and Survey Engineering
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The large-scale and high-intensity mining of coal resources has contributed to the degradation of land resources and ecological environment in the mining area,meanwhile,it promots social progress and economic development in China.This has greatly affected the normal life of the people in the mining area,and brought hidden dangers to the personal and property safety of the people in the mining area and the construction of the mining area.The Hancheng mining area has a long history of mining and is an important part of'the "black belt"of Guanzhong.The mining damage caused by coal mining is widely distributed.In order to effectively control the settlement of the mining area formed by mining,we need to take appropriate methods to scientifically monitor and analyze the surface of the mining area,timely and accurately grasp the development law,and provide a reliable theoretical basis for the safe production of the mining area.The emergence of InSAR technology has provided a new method for mining subsidence in the mining area.Its all-day,all-weather,high-precision,low-cost and continuous space coverage make it widely used and studied in mining subsidence.However,due to the characteristics of rapid subsidence rate and large settlement level,the mining subsidence in the mining area is susceptible to time and space baseline decoherence and atmospheric delay,which makes the InSAR technology limited in the monitoring of land subsidence in the mining area.Therefore,this thesis focuses on the problems of InSAR technology in mining subsidence.Taking Hancheng mining area as an example,interference pattern superposition technology and small baseline set technology were used to monitor and analyze mining subsidence,combined with SA-SVR algorithm to establish mining subsidence.The model,main work and results are expected to be as follows:(1)The 17-view ALOS PALSAR data was processed by Stacking-InSAR technology,and the annual average settlement rate and standard deviation of Xiangshan Mine from January 2007 to February 2011 were obtained.The experiment shows that the mining subsidence in the mining area is consistent with the spatial distribution of the mine,which further demonstrates that the Stacking-InSAR technology has a good application in the monitoring of large-scale deformation in the mining area,and the monitoring results are relatively reliable.(2)The Sentinel-1A data of 22 scenes were processed by SBAS-InSAR technology,and the annual average settlement rate and time series cumulative settlement of Xiangshan Mine were obtained.Combined with the section line and characteristic point analysis of mining tface.the settlement and mining face distribution and mining of mining area were obtained.The situation and the mining footage have good consistency.The monitoring results of SBAS-InSAR technology were verified by GPS observations.The Pearson correlation coefficient was calculated to be 0.998,and the correlation was high.Using rainfall to analyze other induced factors of land subsidence in the Nanyi mining area,the results show that there is no obvious relationship between land subsidence and rainfall in the mining area.(3)The time series InSAR technology and SA-SVR algorithm are used to establish the prediction model of nmining subsidence in mining area.Combined with the time series settlement obtained by SBAS-InSAR monitoring,the points are evenly selected in the direction and tendency of the working face,and the dynamic prediction model of mining subsidence is established.The results were evaluated for accuracy.The results show that the prediction model of mining subsidence based on time series InSAR and SA-SVR algorithm has a coefficient of determination greater than 0.4,good fitting degree and high prediction accuracy,which meets the engineering requirements and provides reliable theoretical basis for mining subsidence in mining areas.
Keywords/Search Tags:Repeated Mining of Multiple Coal Seams, Mining Subsidence, Time Series InAR, Support Vector Regression, Simulated Annealing
PDF Full Text Request
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