Coal mining GPS subsidence monitoring technology and its application

• Published in: Mining science and technology (China) Vol. 21; no. 4; pp. 463 - 467
• Main Authors: Wang, Jian, Peng, Xiangguo, Xu, Chang hui
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-07-2011; Key Laboratory of Land Environment and Disaster Monitoring of SBSM, China University of Mining(&)Technology, Xuzhou 221116, China; State Key Laboratory of Coal Resources and Mine Safety, China University of Mining(&)Technology, Xuzhou 221116, China%Key Laboratory of Land Environment and Disaster Monitoring of SBSM, China University of Mining(&)Technology, Xuzhou 221116, China%School of Surveying(&)Spatial Information Systems. University of New South Wales, Sydney 2052, Australia
• Subjects: Coal mines; DEM; Geographic information systems; Global Positioning System; GPS; GPS基准网; Mining; Monitors; Satellite navigation systems; Subsidence; Subsidence monitoring datum; Support vector machines; SVM; SVM模型; 大地水准面模型; 应用; 数字高程模型; 沉降区; 煤炭开采; 监测技术; GPS; SVM; Subsidence monitoring datum; DEM
• ISSN: 1674-5264; 2212-6066
• DOI: 10.1016/j.mstc.2011.06.001

We proved theoretically that geodetic height, measured with Global Positioning System （GPS）, can he applied directly to monitor coal mine subsidence. Based on a Support Vector Machine （SVM） model, we built a regional geoid model with a Gaussian Radial Basis Function （RBF） and the technical scheme for GPS coal mine subsidence monitoring is presented to provide subsidence information for updating the regional Digital Elevation Model （DEM）. The theory proposed was applied to monitor mining subsi- dence in an Inner Mongolia coal mine in China. The scheme established an accurate GPS reference net- work and a comprehensive leveling conjunction provided the normal height of all GPS control points. According to the case study, the SVM model to establish geoid-model is better than a polynomial fit or a Genetic Algorithm based Back Propagation （GA-BP）neural network. GPS-RTK measurements of coal mine subsidence information can be quickly acquired for updating the DEM.