许疃煤矿非采动沉降监测系统与预测模型
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摘要
近百年来,人类对地下水的过度开采,已经在全球范围内造成了严重的地表沉降现象,给地球自然环境和人类日常生活带来了巨大的危害；对于煤矿工业广场而言,地表沉降导致的工业广场及主副井井架基础的沉降,给矿井生产和安全带来极大的威胁。
本文介绍了变形监测的基本原理和方法,以许疃煤矿为例,建立了工广地表和主副井井架基础非采动沉降监测系统,以国家二等水准测量标准对监测网进行了4期全面观测和9期次级网沉降观测。根据观测数据对基准点进行了稳定性分析。采用拟稳平差方法对首级网观测数据进行处理,并对工作点进行了差异性检验。分别采用固定基准、重心基准和拟稳基准对监测网数据进行处理,选用重心基准作为监测网平差基准,得到了主副井井架基础最大沉降量分别为242.7mm和240.7mm,最大沉降差分别为4mm和4mm。并将钻孔水位动态变化曲线与工广地表下沉曲线进行对比分析表明,地表沉降与水位变化呈现显著的相关关系,但存在一定的滞后效应。
本文介绍了灰色GM(1,1)模型以及预测方法。根据灰色系统理论,对非等间隔数据序列等间隔化,通过模型误差比较优选最佳维数,建立了能反映工程动态变化的灰色GM(1,1)等维新息模型,得到主副井井架基础监测点沉降预测最大残差值分别为0.9mm和1.3mm。经过模型精度评定,预测等级均为1级。预测了2012年1月主副井井架基础监测点的沉降值。
本文基于Microsoft Visual Studio2008编写了监测网平差处理程序和灰色GM(1,1)模型预测程序。
图[35]表[29]参[52]
In the past century, human's uncontrolled exploitation of groundwater has caused serious surface settlement all over the world. As a kind of widespread geological hazards, surface settlement can cause great harm to the earth's natural environment and human daily life. As a coal mine industry square, there is a great threat which was caused by the main and auxiliary shafts' base of mine subsidence which was leaded by the surface settlement in mine production and mine safe.
Taking Xutuan coal mine as an example, the non-mining subsidence monitoring system of the coal mine industry square and the main and auxiliary shafts'base has been build based on principles and methods of deformation monitoring in this paper. According to National second order leveling standard,4times overall observations for subsidence monitoring network has been collected, and the secondary network has been lasted for9periods. The stability analysis of the reference points by the observation data. The quasi-stable adjustment has been used to process the first network observation data, and the difference has been tested for the working points. The fixed datum, gravity datum and quasi-stable datum were used to process the monitoring network data, the gravity datum has been selected as the adjustment datum of the monitoring network. From the results of adjustment data, the maximum settlement of the main and auxiliary shafts'base of mine were242.7mm and240.7mm, the maximum settlement difference were4.0mm and4.1mm. By contrasting the dynamic change curve of the drilling water level with the subsidence curve of the coal mine industry square, the result which the significant and hysteretic relationship between land subsidence and water level variation had been showed in this passage.
The GM (1,1) model and the prediction method were introduced in this passage. According to the theory of grey system, the equal-dimension and new-information model was has been built after Equaled the interval of the non equal interval data sequence and preferred the best dimension through the comparison with the model error. From settlement prediction data, the maximum of predicting data residual error of the main and auxiliary shafts'base of mine were0.9mm and1.3mm. Through the model precision evaluation, the accuracy of model reached the highest level. The settlement value of the main and auxiliary shafts'base of mine in January2012was predicted at last.
The adjustment program which designed to process settlement data and the GM(1,1) prediction program based on Microsoft Visual Studio2008were introduced in this passage.
本文介绍了变形监测的基本原理和方法,以许疃煤矿为例,建立了工广地表和主副井井架基础非采动沉降监测系统,以国家二等水准测量标准对监测网进行了4期全面观测和9期次级网沉降观测。根据观测数据对基准点进行了稳定性分析。采用拟稳平差方法对首级网观测数据进行处理,并对工作点进行了差异性检验。分别采用固定基准、重心基准和拟稳基准对监测网数据进行处理,选用重心基准作为监测网平差基准,得到了主副井井架基础最大沉降量分别为242.7mm和240.7mm,最大沉降差分别为4mm和4mm。并将钻孔水位动态变化曲线与工广地表下沉曲线进行对比分析表明,地表沉降与水位变化呈现显著的相关关系,但存在一定的滞后效应。
本文介绍了灰色GM(1,1)模型以及预测方法。根据灰色系统理论,对非等间隔数据序列等间隔化,通过模型误差比较优选最佳维数,建立了能反映工程动态变化的灰色GM(1,1)等维新息模型,得到主副井井架基础监测点沉降预测最大残差值分别为0.9mm和1.3mm。经过模型精度评定,预测等级均为1级。预测了2012年1月主副井井架基础监测点的沉降值。
本文基于Microsoft Visual Studio2008编写了监测网平差处理程序和灰色GM(1,1)模型预测程序。
图[35]表[29]参[52]
In the past century, human's uncontrolled exploitation of groundwater has caused serious surface settlement all over the world. As a kind of widespread geological hazards, surface settlement can cause great harm to the earth's natural environment and human daily life. As a coal mine industry square, there is a great threat which was caused by the main and auxiliary shafts' base of mine subsidence which was leaded by the surface settlement in mine production and mine safe.
Taking Xutuan coal mine as an example, the non-mining subsidence monitoring system of the coal mine industry square and the main and auxiliary shafts'base has been build based on principles and methods of deformation monitoring in this paper. According to National second order leveling standard,4times overall observations for subsidence monitoring network has been collected, and the secondary network has been lasted for9periods. The stability analysis of the reference points by the observation data. The quasi-stable adjustment has been used to process the first network observation data, and the difference has been tested for the working points. The fixed datum, gravity datum and quasi-stable datum were used to process the monitoring network data, the gravity datum has been selected as the adjustment datum of the monitoring network. From the results of adjustment data, the maximum settlement of the main and auxiliary shafts'base of mine were242.7mm and240.7mm, the maximum settlement difference were4.0mm and4.1mm. By contrasting the dynamic change curve of the drilling water level with the subsidence curve of the coal mine industry square, the result which the significant and hysteretic relationship between land subsidence and water level variation had been showed in this passage.
The GM (1,1) model and the prediction method were introduced in this passage. According to the theory of grey system, the equal-dimension and new-information model was has been built after Equaled the interval of the non equal interval data sequence and preferred the best dimension through the comparison with the model error. From settlement prediction data, the maximum of predicting data residual error of the main and auxiliary shafts'base of mine were0.9mm and1.3mm. Through the model precision evaluation, the accuracy of model reached the highest level. The settlement value of the main and auxiliary shafts'base of mine in January2012was predicted at last.
The adjustment program which designed to process settlement data and the GM(1,1) prediction program based on Microsoft Visual Studio2008were introduced in this passage.
引文
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[37]王利,张双成,李亚红.动态灰色预测模型在大坝变形监测及其预报中的应用研究[J].西安科技大学学报,2005,25(3)：328-332.
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[2]岳建平,田亚林.变形监测技术与应用[M].北京：国防工业出版社,2007.
[3]王晓华,胡友健,柏柳.变形监测研究现状综述[J].测绘科学,2006,31(2)：130-132.
[4]胡明城.国外测绘机构大地测量的新动向[J].测绘科学,2002,25(3)：51-55.
[5]陈基伟.利用GPS-InSAR合成方法进行地面沉降研究的现状与展望[J].测绘科学,2003,28(4)：69-71.
[6]张超.平均间隙法在平面监测网点位稳定性分析中的应用[D].成都：西南交通大学土木工程学院,2007.
[7]黄声享.监测网的稳定性分析[J].测绘信息与工程,2001,26(3)：16-19.
[8l卢冈.稳健s-变换及其确定位移场的有效性[J].武汉大学学报(信息科学版),1987,12(3)：17-27.
[9]崔希璋,於宗俦,陶本藻等.广义测量平差(新版)[M].武汉：武汉测绘科技大学出版社,2001.
[10]谷川.高精度变形测量技术与数据处理方法[D].上海：同济大学土木工程学院,2008.
[1ll潘国荣,王穗辉.多点变形动态灰色模型辨识及预测[J].测绘学报(增刊)2002,31：66-69.
[12]张云,薛禹群.抽水地面沉降数学模型的研究现状与展望[J].中国地质灾害与防治学报.2002,13(2)：1-6.
[13]许烨霜,余恕国,沈水龙.地下水开采引起地面沉降预测方法的现状与未来[J].防灾减灾工程学报.2006,26(3)：352-357.
[14]新华网.十部委规划获国务院批复中国布局地面沉降防治http://news.xinhuanet.com/tech/2012-02/22/c_122739990.htm,2012-2-22.
[15]高永梅.祁东矿工业广场地表沉降监测与预计分析[D].安徽：安徽理工大学,2004.
[16]许延春,耿德庸,中宝宏.淮北临涣矿区地层非采动沉降分析[J].岩土工程学报.1994,16(6)：140-146.
[17]王东攀,李德海.永夏矿区地层非采动沉陷分析[J].矿业工程.2004,2(5)：18-20.
[18]许延春,耿德庸.应用有限元研究临涣矿区地层非采动变形沉降[J].煤炭学报.1995,20：48-54.
[19]许延春,孙晓虎,喻怀君.临涣工业园区非采动沉降安全监测研究[J].矿山测量.2011,3：66-68.
[20]刘环宇,王思敬,倪兴华等.煤矿立井井筒非采动破裂治理新方法设计[J].河海大学学报 (自然科学版).2005,33(2)：190-193.
[21]肖学年等.国家一、二等水准测量规范[M].北京：中国国家标准化管理委员会.
[221JGJ8-2007,建筑变形测量规程.
[23]GB 50026-2007,工程测量规范.
[24]宋孀孀.卧龙湖煤矿主副井井架基础沉降监测研究[D].淮南：安徽理工大学,2009.
[25]潘正风,杨正尧,程效军等.数字测图原理与方法[M].武汉：武汉大学出版社,2004.
[26]葛永慧,夏春林,王列平等.测量平差基础[M].北京：煤炭工业出版社,2007.
[27]陶本藻.自由网平差与变形分析[M].武汉：武汉测绘科技大学出版社,2001.
[28]邱卫宁,陶本藻,姚宜斌等.测量数据处理理论与方法[M].武汉：武汉大学出版社,2008.
[29]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.2008,8：17-20.
[30]刘思峰,郭天榜,党耀国等.灰色系统理论及其应用[M].北京：科学出版社,1999.
[31]邓聚龙.灰色预测与决策[M].武汉：武汉理工大学出版社,1998.
[32]黄声享,尹晖,蒋征.变形监测数据处理[M].武汉：武汉大学出版社,2003：113-114.
[33]傅立.灰色系统理论及其应用[M].北京：科学技术文献出版社,1992：32-71.
[34]李克钢,许江,黄国耀.基于不等时距GM(1,1)模型预测边坡失稳变形[J].地下空间与工程学报.2006,2(6)：988-992.
[35]金义富,朱庆生等.序列缺失数据灰插值推理方法[J].控制与决策.2006,21(2)：236-240.
[36]蒋刚,林鲁生,刘祖德等.边坡变形的灰色预测模型[J].岩土力学.2000,21(2)：244-247.
[37]王利,张双成,李亚红.动态灰色预测模型在大坝变形监测及其预报中的应用研究[J].西安科技大学学报,2005,25(3)：328-332.
[38]郝传才.变形监测网点稳定性分析的若干问题研究[D].四川：西南交通大学,2003：28-35.
[39]王成余,马建良.沉降观测监测网的稳定性分析[J].测绘通报,2010,12：51-53.
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