Monitoring Of Mountain Mining Subsidence And Studying Of Data Processing Methods

Ground subsidence caused by coal mining is a very serious environmental problem, itwill cause surface subsidence, fracture, lead to deformation or even collapse of buildings,create soil profile and deterioration of ecological environment, etc. Western mountains as theimportant coal production base in China, its geomorphic geological environment is complex,the research of mining subsidence law is still inadequate, especially for the on-site monitoringof surface subsidence of mountainous area, there are many technical problems to be solved.This paper analyzes the characteristics of mountainous mining subsidence monitoring.On the premise of meeting the monitoring accuracy and reducing the workload, this paperdiscusses the feasibility of a variety of monitoring methods for mountain mining subsidencemonitoring. In the presence of loss of field observation data, discusses the mathematicalmethods of data interpolation, and combines with engineering instance verified analysis. Themain research results of this paper are as follows1. Comprehensive analysis of a variety of mining subsidence monitoring technology andits applicability, it puts forward the way of using GPS combined with total station combinedoperations at mountain mining subsidence monitoring.2. According to the accuracy requirement of mining subsidence monitoring and theperformance of the used instruments, making use of not cumulative characteristics of GPSmeasurement error i, and considering the amount of angle measuring total station wire edgeerror weights of the size of the impact of monitoring point coordinates, it works out themost of the wire of the total station transfer station after calculating.3. Aiming at the phenomenon of missing data of some observation points measuring,basing on the probability integral and mathematical difference model, it proposed two kindsof data interpolation methods. By examples show that the mathematical interpolation methodused to obtain class observation data is more reliable than probability integral model method.4. As an example of mining subsidence monitoring project of TingNan coal mine204 working face, according to the research results, the mountain mining subsidencemonitoring scheme was made, processed and analyzed the observation data, obtainedinformation of the mining surface movement, and carried on the rational explanation themovement mechanism.