外文翻译-矿井水流突变时期的灰色预警理论和预测.doc
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翻译部分英文原文：Grey Forewarning and Prediction for Mine Water Inflowing Catastrophe PeriodsMA Qihua(马其华) CAO Jian-jun(曹建军)(Key Laboratory of Mine Disaster Prevention and Control，Shandong University of Science and Technology, Qingdao 266510，China)Abstract :Based on the theory of grey system，established GM(1，1)grey catastrophe predict modeI for the first time in order to forecast the catastrophe periods of mine water inflowing(not the volume of water inflowing)After establishing the grey predict system of the catastrophe regularity of 10 monthaverage volume of water inflowing，the grey forewarning for mine water inflowing catastrophe periods was established which was used to analyze water disaster in 400 meter level of Wennan CollieryBased on residual analysis。it shows that the result of grey predict system is almost close to the actual valueAnd the scene actual result also shows the reliability of predictionBoth the theoretical analysis and the scene actual result indicate feasibility and reliability of the method of grey catastrophe predict system.Keywords grey theory,mine water inflowing catastrophe periods，grey forewarning and prediction，GM(1，1)grey prediction model，residual analysis.Introduction Like gas，fire and other mine disasters，water hazard is one of the major disasters in mine construction and production，which causes great loss in personal injury death and economic loss to the country and its people1 One main reason of mine water disaster happening frequently is lacking proper prediction of water dischargeThen preventive measures can not be made in timeIt shows that proper prediction of water discharging is an important link in mine water prevention workSwallet is an open，mplicated system and its stability is greatly affected by geological structure and its constructionSome influence factors are deftnite，but more factors are probability,fuzzy or compound uncertaintyAll these influence factors possess obvious grey property.So it is an urgent problem in correct prediction of mine inflow and its catastrophe periods from engineering circlesGrey system theory is composed of model setting,forecasting，decisionmaking and contro1It is a method for the uncertainty of incomplete information system.The grey system theory has been used in the field of soft foundation settlement forecast3-6.coal and gas outburst prediction7-9 and so on.For Swallet,a typical grey system betwee know (white) and unknown(black)，we can also use grey system theory to predict mine water inflowing catastrophe periodThen emergency preplan and proper preventive measure will be made，which can reduce the damage of mine water bursting.Taking prediction of Wennan coal mine一400 m horizontal water disaster periods for example，the process of applying grey theory is described in water disaster prediction by use GM(1，1)grey predict mode As an attempt,it is in the hope of presenting a new theory and method of mine water disaster prevention1 Introduction of grey disaster prediction theoryThe disaster prediction in this paper is based on the grey svstem10.The main theoretical foundations are in the following。The original data array x(0):x(0)=( x(0)(1), x(0)(2) , x(0)(n)A fixed figure is appointed and the datum in x array which is higher than is an abnormal value point.Then another data array is composed of these abnormal value points picked up from aray x(0).We call the new data array as the upper limit catastrophe array or the upper limit abnormal array.And the lower limit abnormal array is obtained in the same wayFor examplex(0)=( x(0)(1), x(0)(2) , x(0)(3), x(0)(4)=(3,0.7,8,5)Take =1 and define all datum in array x(0) higher than are abnormal value.Then：x(0)(1) , x(0)(3) , x(0)(4) The new data array x (0).which is composed of Equation(1) is expressed as follows:x(0)=( x(0)(1), x(0)(2) , x(0)(3)=3,8,5=( x(0)(1), x(0)(3) , x(0)(4)The Equation(2) shows：3= x(0)(1)= x(0)(1) 118= x(0)(2)= x(0)(3) 235= x(0)(3)= x(0)(4) 34Where ,the symbol“” means“be equivalent to”.The catastrophe prediction is not the value of abnormal datum but the period of abnormal datum appear.The above example shows that the first abnormal value is the first point and the value is 3,as 11. In the same sense.we can find 23 and 34.Our task is to predict the periods of next abnormal value,such as the fourth，fifth and so onIt means that what we care about is not value of x(0)(i) or x(0)(i) but their appearance periodsThrough the grey catastrophe predict model，we will get a numberThe bigger of the number means the further of the next abnormal moment.In other words,the number shows the point of x(0)(i) appearance.Then we can get the corresponding array P,withP=1 2 31 3 4If each doublet data is regard as a point on two dimensional surfaces，a horizontal projection operator P is define.The P is:P=(1,1)= 1 P=(2,3)=2 P=(3,4)=3Then array P=(P(1)，P(2 )，P(n ) is the set of catastrophe periods.It is the catastrophe prediction that we establish GM(1,1) model based on array P.2 Catastrophe periods prediction of water discharging in -400 meter level inWennan Colliery2.1 Summary of the hidden dangers of gob water in Wennan collieryThere are six collieries,such as Shangzhuang Colliery,Shencun Colliery,Shiyang CollieryBeihe Colliery,Shenxi Colliery and Dongdu Colliery,in the western boundary Of Wennan Colliery,Xinwen Mining Group.The gob and roadway of these mines interpenetrate one another,which form a good connected hydraulic unitFor destroying the outcrop coal pillar by these smal1-scale minesmining，the infiltration of precipitation and seepage of surface water greatly recharge into western minesgobThe level of gob water in Wennan Colliery is maintaining the momentum growth.The historical highest water level caught +21.50 m in 2004Because of exceeded mining by Shangzhuang Colliery,the width of boundary pillar was seriously lackMoreover,the stability of boundary pillar was greatly decreased for long-term soaked in high pressure gob waterLarge scale of still water in western minesgob formats the huge high accumu1ated water Of Wennan Colliery,which constituted great water disaster threat to its safety productionFor the huge and high characteristics of gob water，multi-direction and multifield stave control measures were taken by Wennan coal mineSuch as“scattering, plugging and draining”trinity regulation，-50 m level main regulation and control-250 m level assisted regulmion and control，and so onFor application of these measures the threatens of gob water has been all viated effectively,but the volume of gob water discharge in -400 m lever Of Wlennan colliery is still large and the pressure is also high.2.2 -400 m level mine water inflowing catastrophe periods predictionThere are many factors for the volume of mine water dischargingAll these factors are highly complicatedThey are not deterministic or randomness but a kind of fuzzy system stateThe grey prediction of this paper is to predict the next catastrophe moment based on the information we have got，which can instruct ,mine water damage control.The average volume of water discharge in -400m lever of Wennan coal mine from January to October in 2006 are shown in Table 1.Table 1 The month-average volume of water inflowing from January to October in 2006Month12345678910Average volume of water discarging340354314324357361299335328349Based on the statistical analysis in -400m 1ever of Wennan Colliery for many years，the monthaverage volume of water inflowing more than 345m3/h( =345) ) is regarded as abnorma1.And the month with abnormal water inflowing is the catastrophe momentWe can know from Tlable 1 that：x(0)=( x(0)(1), x(0)(2) , , x(0)(10)=(340,354,314,324,357,361,299,335,328,349)The datum in array x(0) satisfying condition x(0) (i)345 is abnorma1Then we can get x(0)based on Equation(2) such that:x(0)= (354,357,361,349)=( x(0)(1), x(0)(2) , x(0)(3), x(0)(4)=( x(0)(2), x(0)(5) , x(0)(6) , x(0)(10)Therefore:P=1 2 3 4 2 5 6 10After doing addition generation of the datum in array pwe will get array p(1) It is：P=-4.5 -10 -18 1 1 1yn=(5,6,10)TAccording to the least square method，parameter vector is := au=(BTB)-1BTyn=0.379752.88937The GM(1，1)model is established based on Equations(3)(6)It is：=9.60860e0.37975k 7.60860Generation model checking is：Reduction data checking is：Then we can compare and analyze model value and value datum The results are shown in Table 2.Table 2 The comparison between predict results of GM(1，1)model and the actual resultsCaculated valueActual value Residual analysisK=14.838453.23%K=26.08866-1.81%K=39.8857101.14%From the reduction data checking of GM(1，1) model above，its residual error of prediction is cornparatively less than 5.The result shows the high re1iability of the built GM(1，1)mode1Based on Equation(7)the next catastrophe moment of water inflowing is:Reduction data is：It was separated by about 3.56743 between 13.56743 and 10If the P(4 ) is regarded as last water inflowing catastrophe period，the next time of catastrophe will be 3.56743 months laterIt will be after January of20072.3 Analysis of grey prediction result of water inflowing catastrophe in -400 m levelThe residual analysis results(Table 2) shows the fiting accuracy is high satisfactory(1ess than 5). Meanwhile，after measurement on field，the volume of water inflowing is less and relatively stable between November,2006 and January,2007，while the water inflowing volume in February,2007 is obviously larger and has fiend of further increasingIt explains in further steps that the predict result is in concordance withthefact3 Conclusions and recommendations3.1 ConclusionThe gray theoretical GM(1，1)model for predicting mine water inflowing catastrophe periods has high reliability with reduction data residual checkingFor the predict result is in concordance with the factthe model can exactly represent objective existence and development tendency of mine water inflowing catastrophe periodsThe grey prediction method brings theoretical foundation for forewarning and prediction of mine water disaster.3.2 RecommendationsThe study ofthis paper ofers a new method and approach to predict mine water disasterBut there is a problem we should pay close attention to which is the grey system prediction based on the finite information. Though the objective existence of the mutation law is reflected in mine water inflowing. Further research in some aspects is expectedThe diversity and complexity of catastrophe conditions of mine water inflowing requires that the grey parameters of catastrophe model should be endowed with accurate practical significances.Meanwhile，the establishment of grey predicts system is not once and for al1. The accuracy of predic result is based on the amount and reliability of information we have had. We think it is essentially accurate and reliable for predicting the next catastrophe period after a new grey prediction system has been estab1ished To predict many times of catastrophe momentswith one catastrophe model is not advocated. We should modify grey parameters in time and establish new prediction model based on the risk of new information we have got. Then the credibility of prediction result can be greatly improved with the new mode1References1Hu WeiyueThe key technical problems of coal mine water hazard control at present stageJ.Coal Geology& Exploration，2005，33(S1)：27 -302Zhao KejianStudy on reliability appraisal of the structures through grey system theoryD. Tianjin：Tianjin University,20053Zeng Chao，Tang ZhonghuaStudy of the application of grey model in the prediction of soft soil roadbed settlementJSite Investigation Science&Technology,2002 (1)：16194Jiang Gang，Lin Lusheng，Liu Zude，et a1Prediction grey model for slope displacementJRock and Soil Mechanics，2000，21(3)：244 2475Lei Xuewen，Bai Shiwei，Meng QingsbanThe application of grey forecasting to analysis soft foundation settlementsJRock and Soil Mechanics，2000，21(3)：145 147 6Guo Hongrnei，Ma PeixianApplication of the grey theory in forecasting the finally subsides of compound ground distortsJGeotechnical Investigation& Surveying.2001(1)：1416 7Wu Aiyou，Xiao Hongi，Wang Conglu，et a1Establishment and application of weights and association model based on coal and gas outburst controlled factors assessmentJJournal of China Coal Society,2005，30(1)5862.8Wu Aiyou，Tian Yunli，Song Yi，et a1Application of the grey theory for predicting the amount of mine gas emission in coal mineJJournal of China Coal Society,2005，30(5)：589592 9Zhang Ruilin，Liu Xiao，Zheng LijunThe grey dynamoic model for predicting gas gushingJChina Mining Magazine，2006，15(12)：l10 1 12 10Deng JulongGray system essential methodM.Wuhan：Huazhong University of Science and Technology Press,1996中文译文：矿井水流突变时期的灰色预警理论和预测（矿井灾害预防与控制重点实验室，中国山东科技大学青岛266510）摘要：首次以基于灰色系统理论建立的GM（1,1）灰色突变预测模型为矿井水突变时期水流做预测（不是做水流量的预测）。矿井水流突变时期的矿井灰色预警模型成立以后，被用来分析汶南煤矿-400米水平的水害情况。根据残差分析结果显示，灰色理论系统预测的结果跟实际的结果几乎一致。现场实际测量的结果也显示出灰色理论系统的预测的可靠性。实验理论分析和科学实验的现场结果都表示出矿井水流突变时期的灰色理论预测和预警的方法的可行性和可靠性。关键词：灰色理论、矿井水流灾变时期、灰色理论系统的预警和预测、GM（1,1）灰色理论预测模型、残差分析。前言像煤层气，火灾和其他矿山灾害一样，水害是矿山建设和生产的主要灾害之一，是造成人身伤亡和人员死亡，是给国家和人民造成巨大经济损失的主要原因之一。矿井水害频繁发生的主要原因是缺乏适当的矿井水流量预测，其次还在于矿井水害预测的方法不能及时的应用。有数据表明排放水的正确预测是矿井水害防治工作的重要环节。Swallet是一个开放的复杂的系统，它的建设性和稳定性受到地质构造的极大的影响。它的影响因素有的明确的，但是更多的因素是模糊的是复合性的是不确定性的。所有的这些因素都具有灰色性质，因此它是工程界在矿井水突变时期水量预测的迫切需要解决的问题。灰色理论系统的组成是由模型设置，预测和决策组成的。它是不完全信息的不确定性方法的系统。灰色理论系统已经被应用于软岩沉降预测和煤与瓦斯突出预测等领域。对于Swallet ，典型的灰色系统之间的了解（白色）和未知（黑色），我们也可以使用灰色系统理论预测将矿井水流入灾难时期.然后采取应急预案和适当的预防措施，可以减少煤矿突水所造成的损害。以汶南煤矿-400米水平为例做的矿井水突变时期灰色理论预测，应用灰色理论系统过程中使用GM（1,1）灰色预测模型作为一种新的尝试，这种尝试希望能够为矿井水害防治提出新的理论与方法。1灰色灾害预测理论引言本文中的灾害预测是基于灰色系统10。以下为主要理论基础：灰色预测理论原始数据阵列为x(0):x(0)=( x(0)(1), x(0)(2) , x(0)(n)任命一个固定的数字，高于基准的数字，作为X数组的一个异常值点。然后再将这些异常值点从x(0)阵列取出然后组成另一个阵列。我们称这样的阵列为上限灾难阵列或上限异常阵列。同时，以同样的方式获得下线异常阵列。例如：x(0)=( x(0)(1), x(0)(2) , x(0)(3), x(0)(4)=(3,0.7,8,5)取 =1 然后定义数组x(0)的所有基准高于异常值。然后得到：x(0)(1) , x(0)(3) , x(0)(4) 新的数据数组 x (0)由方程（1）组成如下表式：x(0)=( x(0)(1), x(0)(2) , x(0)(3)=3,8,5=( x(0)(1), x(0)(3) , x(0)(4)方程（2）表示为：3= x(0)(1)= x(0)(1) 118= x(0)(2)= x(0)(3) 235= x(0)(3)= x(0)(4) 34这里“”符号表示“相当于“。水害灾难的预测没有异常的基准值，但是期间出现异常基准值。根据上面的例子不难看出，异常值的第一价值是第一点，它的值是3，也就是11。用同样的方法我们可以找出23、34。我们的任务是预测异常值区间，例如第四、第五等。也就是说我们真正关心的并不是上述方程的值，而是关心异常值点出现的时期。通过灰色突变预测模型，我们会获得一个值，值越大就意味着未来的异常时刻更加接近。换句话说也就是将x(0)(i)的值挑选出来，组成一个新的阵列P：P=1 2 31 3 4如果每个双重数据是作为一个二维表面上的点方面，水平投影算子定义为P。P表示为：P=(1,1)= 1 P=(2,3)=2 P=(3,4)=3然后得出P=(P(1)，P(2 )，P(n )是一套矿井水突变时期突变区间。这就是基于阵列和GM（1,1）模型建立起的突变预测。2汶南-400米水平矿井水突变时期的涌水量预测2.1汶南煤矿采空区水的隐患简介在新汶矿业集团汶南煤矿的西部边界地区有6个煤矿，如庄矿，深村煤矿，石羊河煤矿、北和煤矿，苏申锡煤矿和东渡煤矿。这些煤矿矿山采空区和巷道相互渗透，形成了良好的连接的液压装置。由于矿山开采时破坏了小型煤层露头，大气降水和地表水渗透并充填了西部采空区。汶南煤矿采空区的积水一直保持增长的势头。在2004年，汶南煤矿采矿区积水达到历史最高水平+21.5m。由于庄矿的过度超采，边界煤柱的宽度严重不足。此外，边界煤柱长期浸泡在高压力采空区水中，煤柱的稳定性大大的降低。大量的水还在汶南煤矿的西部积聚，巨大的高压力水积聚在采空区对煤矿的安全生产构成了极大的威胁。根据采空区积水的多方向性、水位高和水量巨大的特点，汶南矿决定采区围岩控制措施控制采空区积水。例如“散射，堵漏和排水”三位一体的调控措施，-50米作为主要调控，-250米做辅助调控等等措施。应用了这些措施，矿区的采空区积水威胁得到了有效的缓解但是汶南-400米水平的采空区水排量依然很大，压力也非常高。2.2 -400 m水平矿井水流入突变时期预测影响矿井水流量的因素有很多，而这些因素又通常非常的复杂。这些因素具有不确定性或随机性，是一种模糊的系统状态。本文所提到的灰色理论预测是预测未来矿井水突变时期，根据我们得到的数据利用灰色理论系统，它可以对矿井水的防治起到指导作用。汶南煤矿-400米水平2006年一月到十月的平均水排量如表1所示表1 2006年1月到10月的平均水量月份12345678910平均水流量340354314324357361299335328349在汶南煤矿-400米水平多年的统计分析基础上，月排水量超多345立方米每小时的被认为是异常水流，而该月也被认为是矿井水的突变时期。我们可以从表1中看出：x(0)=( x(0)(1), x(0)(2) , , x(0)(10)=(340,354,314,324,357,361,299,335,328,349)在阵列x(0)取出满足条件：x(0) (i)345的，取出的数据位异常值，然后我们可以再方程（2）的基础之上得到x(0)如x(0)= (354,357,361,349)=( x(0)(1), x(0)
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