童亭煤矿工业广场地表沉降监测与预测
发布时间：2018-08-22 11:44
【摘要】：近年来,两淮和徐州矿区很多工业广场地表发生了不同程度的沉降,工业广场地表发生发生沉降时,工业广场地表上的建(构)筑物和井筒等也遭到了一定的破坏,给煤矿的生产和安全带来了极大的威胁。本文针对童亭煤矿工业广场地表进行沉降监测,并建立预测模型。 本文介绍了沉降监测的基本知识,以童亭煤矿为例,建立了工业广场地表沉降监测系统。按照国家二等水准测量方法对基准网和首级网进行了3次全面观测,对次级网进行了17期沉降观测。基准网选取重心基准,采用秩亏自由网平差方法,并对基准点进行了稳定性分析。首级网选用固定基准,采用经典平差方法,并对工作点进行了差异性检验。经严密平差处理与分析得出,在观测期内：工业广场地表平均累积沉降量为12.4mm；主井井架基础平均累积沉降量为12.6mm；煤仓1、煤仓2、煤仓3的最大倾斜变形分别为：0.12mm/m.0.15mm/m.0.13mm/m。按照相关规范主井井架基础和3个煤仓在整个观测期内均处于安全状态。 本文介绍了灰色系统模型和时间序列模型的建模原理和预测方法等,并以Visual Basic6.0为开发环境设计编制了童亭煤矿工业广场地表沉降监测预测系统。依据灰色系统理论,选取最佳维数,建立了GM(1,1)等维新息模型,得到工业广场地表6个特征点(ZN2、ZJK、1#、E8、W2、E3)平均残差值为0.2mm,模型精度等级为2级以上,各特征点第18期(2014年12月)的预测值依次为：-11.5mm、.3.7mm、-10.8mm、-13.9mm、-13.3mm、-11.6mm,预测精度有待进一步验证。依据时间序列理论,建立了AR(p)模型,得到工业广场地表6个特征点(ZN2、ZJK、1#、E8、W2、E3)平均残差值为0.4mm,具有较高精度。根据现有工业广场地表沉降监测资料分析得出：两种模型的精度均能满足要求,但灰色系统模型的平均残差和中误差较小,在童亭煤矿工业广场地表沉降监测预测系统中灰色系统模型略优于时间序列模型。
[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.
【学位授予单位】：安徽理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P642.26
本文编号：2197000
[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.
【学位授予单位】：安徽理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P642.26
【参考文献】
相关期刊论文 前10条
1 李井春;夏立福;张正禄;;监测网参考基准的选取与统一[J];测绘通报;2008年08期
2 黄兵杰;张妍;余咏胜;;变形监测网合适参考系的确定与稳定性分析[J];测绘与空间地理信息;2011年06期
3 潘国荣;谷川;;形变监测数据组合预测[J];大地测量与地球动力学;2006年04期
4 陈定元;钟金标;;模糊序列的GM(1,1)建模[J];工程数学学报;2010年03期
5 张成军;陈炜;范晓华;;时序相似集合预报法及其在天气预报中的应用技巧[J];甘肃联合大学学报(自然科学版);2009年02期
6 刘少聪;徐鹏;赵启龙;;基于改进GM(1,1)模型的Vb程序实现及其应用[J];工程地球物理学报;2012年04期
7 关延峰;;精密二等水准测量质量控制研究[J];测绘与空间地理信息;2013年04期
8 潘宇;姜晓磊;杨泰;王列平;;等维新息模型在矿井井架基础沉降中的应用[J];安徽理工大学学报(自然科学版);2011年02期
9 韩路跃,杜行检;基于MATLAB的时间序列建模与预测[J];计算机仿真;2005年04期
10 顾海燕;;时间序列分析在人口预测问题中的应用[J];黑龙江工程学院学报;2007年03期
相关博士学位论文 前1条
1 范国庆;工程变形监测数据处理及其在越南的应用研究[D];武汉大学;2012年
，本文编号：2197000
本文链接：https://www.wllwen.com/kejilunwen/diqiudizhi/2197000.html
