童亭煤礦工業(yè)廣場(chǎng)地表沉降監(jiān)測(cè)與預(yù)測(cè)
[Abstract]:In recent years, the ground surface of many industrial squares in the Lianghuai and Xuzhou mining areas has been settled to varying degrees. When the ground surface of the industrial square is subsided, the construction (construction) and wellbore on the industrial square surface have also been damaged to a certain extent. It poses a great threat to the production and safety of coal mines. In this paper, the ground subsidence of Tongting Coal Mine Industrial Square is monitored and a prediction model is established. This paper introduces the basic knowledge of subsidence monitoring. Taking Tongting Coal Mine as an example, the ground subsidence monitoring system of Industrial Plaza is established. According to the national secondary leveling method, three comprehensive observations were made on the datum network and the first network, and 17 settlement observations were carried out on the secondary network. The barycenter datum is selected and the rank deficient free net adjustment method is used to analyze the stability of the datum. The first level net selects fixed datum, adopts the classical adjustment method, and carries on the difference test to the working point. Through strict adjustment and analysis, it is concluded that during the observation period, the average cumulative settlement of the ground surface of Industrial Square is 12.4mm, the average cumulative settlement of the main Derrick foundation is 12.6mm, and the maximum inclined deformation of bunker 1, bunker 2, bunker 3 is respectively 0.12mmm.0.15mmm.0.13mmmm. The foundation of the main well Derrick and the three coal bunkers are in safe condition during the whole observation period according to the relevant codes. This paper introduces the modeling principle and prediction method of grey system model and time series model, and designs the ground subsidence monitoring and forecasting system of Tongting Coal Mine Industrial Square with Visual Basic6.0 as the development environment. According to the grey system theory and the optimum dimension, the GM (1K1) equal dimensional innovation model is established. The average residual value of the six characteristic points (ZN2ZJKGQ1#E8W2W2E3) of the industrial square is 0.2mm, and the precision grade of the model is more than 2 grades. The predicted values of each feature point in phase 18 (December 2014) are: -11.5mm-1. 3.7mm/ -10.8mm-1 -13.9mm + -13.3 mm + -11.6mm respectively. The prediction accuracy needs to be further verified. Based on the theory of time series, the AR (p) model is established, and the average residual value of the six characteristic points (ZN2ZJK1 #E8W2W2E3) of Industrial Plaza is 0.4mm, which has a high accuracy. According to the existing monitoring data of ground subsidence in Industrial Plaza, it is concluded that the precision of the two models can meet the requirements, but the average residual error and the median error of the grey system model are small. In the ground subsidence monitoring and forecasting system of Tongting Coal Mine Industrial Square, the grey system model is slightly better than the time series model.
【學(xué)位授予單位】:安徽理工大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2015
【分類號(hào)】:P642.26
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