用户名: 密码: 验证码:
基于GIS的矿井突水水源综合信息快速判别系统
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
近年来,随着煤炭开采深度、开采强度、开采速度、开采规模等不断增加,煤炭开采受地下水威胁、危害日趋严重。准确、快速的判别突水水源,是快速采取针对性的治水措施的基础,是确保矿井煤矿安全生产的一项关键技术。本文基于ArcSDE空间数据引擎技术和Microsoft SQL Server设计建立矿井突水水源判别综合信息空间数据库;引入空间数据挖掘技术,将其应用于矿井地下水分析中,并基于Voronoi图方法和DEM方法挖掘了矿井地下水化学类型分布规律和地下水水化学与构造的空间关联规则;研究了常用的矿井突水水源判别模型,重点研究了采用F值定权的模糊综合判别模型,并提出了基于GIS的水温识别矿井突水水源的判别方法,并以此为基础构建了集成水位、水化学、水温于一体的矿井突水水源的综合信息判别模型;基于GIS开发了矿井突水水源综合信息快速判别系统。
     本文取得的主要结论及成果:建立了简单实用的矿井突水水源综合信息识别流程体系;建立了矿井突水水源判别综合信息空间数据库;潘一矿煤系水具有在研究区北部沿潘集背斜走向一带状区域主要为Cl-K+Na型水,南部一集中区域为HCO3-K+Na型水,其他为HCO3·Cl-K+Na型水的分布特点;新生界下含水具有水化学类型为单一的Cl-K+Na型水的特点;得到了研究区内与潘集背斜距离近的煤系水样的HCO3-浓度值小等规则;在潘一矿,贝叶斯判别准确率为87.23%,神经网络判别准确率为87.23%,灰色关联分析判别结果为80.43%,F值定权的模糊综合评判判别准确率为93.48%,综合信息判别结果表明,水温判别对水质判别已经起到了一定的辅助作用,建立的判别模型具有较好的判别效果;基于GIS开发的系统实现了对相关的各种空间数据和属性数据的管理、矿井突水水源的综合信息判别以及空间数据的三维可视化等功能,系统具有较高的应用价值。
     本文的创新之处:
     (1)将空间数据挖掘技术应用于矿井地下水分析中,并基于Voronoi图方法和DEM方法挖掘了矿井地下水化学类型分布规律;
     (2)提出了基于GIS的水温识别矿井突水水源的判别方法,并构建了集水位、水化学、水温于一体的矿井突水水源的综合信息判别模型;
     (3)开发了简便、快速、实用的基于GIS的矿井突水水源综合信息快速判别系统;
In recent years, with the increase of the coal mining depth, intensity, rate and the exploitation scale, coal mining is under the serious threat of groundwater. Discriminating the source of water-inrush exactly and quickly is the basis of taking countermeasures for water-inrush control, and also is a key technology to ensure the mine safety production.
     Based on the technology of ArcSDE and Microsoft SQL Server, this paper designed and established a comprehensive information spatial database for discrimination of water-inrush source; spatial data mining technology was introduced and then applied it to the analysis of mine groundwater, and based on Voronoi diagram method and DEM method mined the distribution rules of the hydrochemical types and the spatial association rule of groundwater chemistry and structure; the common models in water-inrush source discrimination was studied, and the fuzzy discrimination model based on F-value weighting was focused on, then a identification method of mine water-inrush source with water temperature based on GIS was proposed, and based on these, discrimination model of mine water-inrush source with comprehensive information which is an integration of water level, water chemistry and water temperature was established; a GIS-based discrimination system of mine water-inrush source with comprehensive information was developed.
     The main conclusions and results of this paper are as follows: a simple and practical flow system which can identify mine water-inrush source with comprehensive information was established; a comprehensive information spatial database for discrimination of water-inrush source was constituted; the distribution rules of the coal measure aquifer water in Panyi were found, such as the main water-type is Cl-K+Na in Panji anticlinal trend belt area in the north of Panyi, a concentrative region of south in the researh area is HCO3-K+Na, and other areas are HCO3-Cl-K+Na, the Cenozoic bottom aquifer water is single type of Cl-Na+K; rules such as the HCO3- values of samples in coal measure water which are close to Panji anticline are low were obtained; in Panyi mine, the discrimination accuracy rates of Bayes, neural network, analysis of gray related degree; method and fuzzy comprehensive evaluation method with F-value weighting are 87.23%, 87.23%, 80.43% and 93.48%. The results of comprehensive information discrimination show that water temperature discrimination has played a supplementary role to the water quality discrimination, and the model have good effects. The system developed based on GIS realize the management for a variety of related data and attribute data, the discrimination of mine water-inrush source, the three-dimensional visualization of spatial data, and also other functions. It has better actual application value.
     The innovations of this article are as follows:
     (1)Spatial data mining technology was applied to analyze the groundwater of mine, and based on Voronoi diagram method and DEM the distribution rules of the chemical types of groundwater were mined;
     (2)A identification method of mine water-inrush source with water temperature based on GIS was proposed and discrimination model of mine water-inrush source with comprehensive information which integrated water level, water chemical and water temperature was established;
     (3)A simple, rapid and practical GIS-based system for mine water-inrush source discrimination with comprehensive information was developed.
引文
[1]杨大明.我国煤矿安全生产的现状、特点与对策措施[J],科技导报,2003,1.
    [2]王则才.国庄矿北大巷突水通道分析[J] ,煤田地质与勘探,2001,29(6):46-47.
    [3]孟召平,易武,兰华,王萌.开滦范各庄井田突水特征及煤层底板突水地质条件分析[J].岩石力学与工程学报,2009,28(2):228-235.
    [4]David Laurence. Optimisation of the mine closure process[J]. Journal of Cleaner Production ,2006,14:285-298.
    [5]罗大贤,杨正东.低压限量壁后注浆技术[J].煤矿设计,2001, (02):29-30.
    [6]郭启文.煤煤矿重大水害快速治理技术:注浆堵水的实践与认识[M].北京:煤炭工业出版社,2005.
    [7]Wang M, Zhang B. Control of the water bursting hazards in northern China type coal mines[J]. Geology, 1995, 41(6): 553-558
    [8]陆守一.地理信息系统.北京:高等教育出版社[M].2004,8.
    [9]黄杏元,马劲松.地理信息系统概论(修订版) [M].北京:高等教育出版社[M].2001.
    [10]高俊岩,王小英,毋海燕.浅析GIS在环境影响评价中应用.科技情报开发与经济,2005,(17):126-128.
    [11]宫辉力.地理信息系统(GIS)在地下水领域应用的一些新进展[J].工程勘察,1996,(1):28-31.
    [12]张瑞钢.基于GIS的潘一矿地下水环境特征分析及突水水源判别模型[D].合肥工业大学硕士论文.2008.6.
    [13]武强,解淑寒,裴振江,马积福.煤层底板突水评价的新型实用方法Ⅲ——基于GIS的ANN型脆弱性指数法应用[J].煤炭学报,2007,32 (12):1301-1306.
    [14]Wu Q, Zhou W F. Prediction of groundwater inrush into coal mines from aquifers underlying the coal seams in China: vulnerability index method and its construction[J]. Environ Geol, 2008, 56(2):245–254.
    [15]Wu Q, Zhou W F, Wang J H. Prediction of groundwater inrush into coal mines from aquifers underlying the coal seams in China: application of vulnerability index method to Zhangcun Coal Mine, China[J]. Environmental Geology, 2009, 57(5): 1187-1195.
    [16]凌良辅.以“下三带”理论对开采受承压水威胁煤层的探讨[J].科技情报开发与经济,2003,(10):192-163.
    [17]李白英.防矿井底板突水的“下三带”理论及其发展与应用[J].山东矿业学院学报(自然科学版),1999,18 (4):11-18.
    [18]施龙青,宋振骐.肥城煤田深部开采突水评价[J].煤炭学报,2000,25(3):273-277.
    [19]靳德武.采煤工作面煤层底板突水预报泛决策分析理论研究综述[J].焦作工学院学报(自然科学版),2000,19(4):246-249.
    [20]Zhang, J C. Investigations of water inrushes from aquifers under coal seams[J].International Journal of Rock Mechanics and Mining Sciences, 2005, 42(3): 350-360.
    [21]孔海陵,陈占清,卜万奎,王波,王路珍.承载关键层、隔水关键层和渗流关键层关系初探[J].煤炭学报,2008,33(5):485-488.
    [22]杜春志,王路珍,陈荣华,孔海陵.长壁综采工作面底板隔水关键层力学性能分析[J].矿业安全与环保,2008,35(3):51-53,58.
    [23]王广军,杨本水,阎昌银.3222工作面突水灾害与治理技术[J] .中国煤田地质, 2002,14(4):6-7.
    [24]杨本水,王从书,阎昌银.祁东煤矿突水灾害成因分析[J] .煤田地质与勘探,2003,31(1):31-33.
    [25]陈忠胜,杨思光,张成银.三河尖煤矿21102面底板奥灰特大突水原因及治理[J].煤田地质与勘探,2005,33(2):44-46.
    [26]杜希山,张崇良,茹卫平,等.北宿煤矿含水层水化学特征分析[J].煤矿现代化, 2006,1:61-62.
    [27]刘现宣.利用水化学特征判断煤矿涌突水水源[J].煤炭科技,1999,3:15-16.
    [28]刘文明,罗巨安,等.潘谢矿区矿井突水水源的QLT法判别[J].中国煤炭,2001, 27(5):31-34.
    [29]李志锋,翟振.煤矿矿井突水水源的Fisher判别模型[J].矿业快报,2008,24(9):57-58.
    [30]刘传韬,赵庆民,张忠.底板突水的专家评分—层次分析预测与评价[J].矿山压力与顶板管理,2001(4):97-99.
    [31]刘文韬,张文泉,李加祥.用层次分析-模糊评判进行底板突水安全性评价.煤炭学报,2000,25(3):278-282.
    [32]余克林,杨永生,章臣平.模糊综合评判法在判别矿井突水水源中的应用[J].金属矿山,2007(3):47-50.
    [33]孙亚军,杨国勇,郑琳.基于GIS的矿井突水水源判别系统研究[J].煤田地质与勘探,2007(2).
    [34]李其康.灰色局势综合评判法在煤矿突水水源判别中的应用[J].中国煤炭地质,2008,20(7):47-48.
    [35]张宏刚.灰色局势综合评判法在突水水源判别中的应用[J].水利科技与经济, 2007,13(12):887-888.
    [36]高卫东.灰色局势决策方法在矿井突水水源判别中的应用[J].矿业安全与环保,2007,34(6):47-49.
    [37]魏永强,梁化强,任印国,刘伟.神经网络在判别煤矿突水水源中的应用[J].江苏地质,2004,28(1):36-38.
    [38]张瑞钢,钱家忠,马雷,覃华.可拓识别方法在矿井突水水源判别中的应用[J].煤炭学报,2009,34(1):33-38.
    [39]桂和荣,陈陆望.矿区地下水水文地球化学演化与识别[M].北京:地质出版社, 2007.
    [40]Babiker I S, Mohamed M A A, Hiyama T. Assessing groundwater quality using GIS[J]. Water Resources Management, 2007, 21(4): 699-715.
    [41]El-Naqa A, Hammouri N, Kuisi M. GIS-based evaluation of groundwater vulnerability in the Russeifa area, Jordan[J]. Revista Mexicana De Ciencias Geologicas, 2006, 23(3): 277-287.
    [42]Wu Q, Xu H, Zhou W F. Development of a 3D GIS and its application to karst areas[J]. Environmental Geology, 2008, 54(5): 1037-1045.
    [43]Radu D, Ilinca C M. GIS database for groundwater integrated management[C]. Proceedings of the 2nd International Conference on Environmental and Geological Science and Engineering 2009, 96-100
    [44]Qiang Wu,Hua Xu,Wei Pang. GIS and ANN coupling model:an innovative approach to evaluate vulnerability of karst water inrush in coalmines of north China[J]. Environ Geol,2008,54: 937-943.
    [45]Feng Q Y, Zhou L, et al. Prediction of water inrush from the seam roof in coal mine based on multi-factor analysis of GIS[J]. Progress in Mining Science and Safety Technology, 2007, Pts A and B: 294-299.
    [46]武强,董书宁,张志龙.矿井水害防治[M].徐州:中国矿业大学出版社,2007.
    [47]武强,张志龙,马积福.煤层底板突水评价的新型实用方法Ⅰ—主控指标体系的建设[J].煤炭学报,2007,32(1):42-47.
    [48]袁文华,桂和荣.任楼煤矿地温特征及在水源判别中的应用[J].安徽理工大学学报(自然科学版),2005,25(14):9-11.
    [49]桂和荣.皖北矿区地下水水文地球化学特征[D].中国科学技术大学博士学位论文, 2005.
    [50]段中稳.矿井突水水源判别与涌水量计算及其防治研究[D].安徽理工大学工程硕士学位论文,2004.
    [51]潘国营,王素娜,孙小岩,范书凯.同位素技术在判别矿井突水水源中的应用[J].矿业安全与环保,2009,36(1):32-34.
    [52]吴信才.空间数据库[M].北京:科学出版社,2009.
    [53]刘洪岐,宫辉力.基于ArcSDE和SQL Server2000的洪涝灾害救助决策支持系统空间数据库设计研究[J].首都师范大学学报(自然科学版),2008,29(2):65-71.
    [54]钟世杰,陈锁忠,姜许辉.基于ArcSDE的矿井水文地质数据库构建研究[J].能源技术与管理,2008,(5):108-110.
    [55]李德仁,王树良,李德毅.空间数据局挖掘理论与应用[M].北京:科学出版社,2006.
    [56]马荣华,蒲英霞,马晓东. GIS空间关联模式发现[M].北京:科学出版社,2007.
    [57]邸凯昌,李德仁,李德毅.空间数据挖掘和知识发现的框架[J].武汉测绘科技大学学报,1997, 22 (1):328-332.
    [58]王大纯,张人权,史毅虹等.水文地质学基础[M].北京:地质出版社,1995.
    [59]冯仲科,郭清文,朱萍. Voronoi图—泰森多边形法在角规测树中的应用[J].林业资源管理,2006,(3):44-47.
    [60]周海燕.空间数据挖掘的研究[D].中国人民解放军信息工程大学博士学位论文, 2003.
    [61]曹爱红,王映龙,唐建军.Voronoi图在新能源场选址中的应用[J].安徽农业科学, 2008,36(34):15137-15138.
    [62]冯亮,刘德钦,马维军.基于Voronoi图的人口普查区的划分技术研究[J].测绘科学,2009,34(2):97-99.
    [63]尹宝才,徐振华,孔德慧,肖小芳.基于Voronoi图的实时人群路径规划[J].北京工业大学学报,2009,35(8):1116-1121.
    [64]李志林,朱庆.数字高成模型[M].武汉:武汉大学出版社,2003.
    [65]Shirakawa T, Adamatzky A, et al. On Simultaneous Construction of Voronoi Diagram and Delaunay Triangulation by Physarum Polycephalum[J]. International Journal of Bifurcation and Chaos, 2009, 19(9): 3109-3117.
    [67]何婧,王丽珍,邹力鹍.基于云南气象数据的空间关联规则挖掘[J].计算机工程与应用,2003,34:187-190.
    [68]章文波,陈红艳.使用数据分析及SPSS12.0应用[M].北京:人民邮电出版社,2006,208.
    [69]徐忠杰,杨永国,汤琳.神经网络在矿井水源判别中的应用[J].煤矿安全,2007,38(2):4-6,17.
    [70]魏加华,李宁等.人工神经网络在水源地影响评价中的应用[J].地球学报,2001,22(3):283-288.
    [71]田景文,高美娟.人工神经网络算法研究及应用[M].北京:北京理工大学出版社,2006.
    [72]刘思峰,党耀国,方志耕,等.灰色系统理论及其应用[M].北京:科学出版社,2004.
    [73]胡友彪,郑世书.矿井水源判别的灰色关联度方法[J].工程勘察,1997(1):33-36.
    [74]岳梅.判断矿井突水水源灰色系统关联分析的应用[J].煤炭科学技术,2002,30(4):37-39.
    [75]贲旭东,郭英海,解奕伟,沈玉林,张传风,平立华.模糊综合评判在矿井突水水源判别中的应用及探讨[J].矿业安全与环保,2006,33(3):57-59.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700