煤矿突发水灾害预警系统设计
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摘要
随着我国经济的飞速发展,煤炭的需求日益增长,煤矿的生产任务不断增加,煤矿安全问题也变得尤为突出。近年来,我国的煤矿事故死亡人数一直高居世界之首,究其原因除了我国煤矿的基础安全设施薄弱、人员安全意识差之外,还与我们对煤矿安全管理的预警工作开展缓慢有关。煤矿的地理特点致使其在事故救援方面存在诸如破坏程度大、应急救援困难等不利因素,但与其他的煤矿事故不同,如果能提前预测煤矿突发水灾害,可以采取排水降压、预留煤柱等防治措施避免突水事故的发生或者减小其造成的损失。煤矿突发水灾害预警系统能够通过科学的手段和方法预测突水事故,降低突水事故的发生频率,减少煤矿人员伤亡,提高企业经济效益,提升政府在公众心目的形象,具有较高的经济和社会效益。目前,能够在企业中实际运用的煤矿突发水灾害预警系统较少,对此的研究大都停留在理论阶段,实用性需要进一步改进。
本文提出煤矿突发水灾害预警系统的设计,其主要包括数据监测和预测两个重要模块和用户管理、数据查询、事后信息录入三个辅助模块。文章首先以煤矿突发水灾害机理为基础,分析突水的主要影响因素,建立煤矿突发水灾害预警系统的监测指标体系,并运用Access数据库、VB,设计煤矿突发水灾害预警系统的登陆、数据输入、查询与用户管理界面。
其次通过对煤矿突发水灾害常规算法的对比分析,选择BP神经网络集成模型建立煤矿突发水灾害预测模型,并根据突水量与矿井最大排水量间的关系,对煤矿突发水灾害进行等级划分,确定预警界限值,将matlab、Access数据库和VB相结合,设计煤矿突发水灾害预警系统的预测、预报和事后信息录入界面。
最后通过对平顶山X.煤矿考察和监测,选取该矿4个点作为监测点,将数据输入预警系统,根据预警系统的输出做出相应措施,验证了煤矿突发水灾害系统的可操作性与适用性，能够为企业监测突发水灾害可能性,将突发水灾害事故扼杀于萌芽,降低事故发生频率和企业安全生产成本,提高企业的经济和社会效益。
With the rapid development of China's economy, growing demand for coal and increasing coal production task, the safety problem of coal mine has become particularly prominent. In recent years, the death toll of China's coal mine accident has been ranked first in the world, not only the basis of safety facilities are inadequate for China's coal mine, and staff safety awareness is poor, but also our early warning of coal mine safety management is carried out with a slow pace. The accident rescue has unfavorable factors such as the extent of the damage, emergency rescue difficulties, because of Geographical characteristics of the coal. But it is different from other coal mine accidents, if the water disaster of coal mine can be predicted in advance, water drainage, setting aside coal pillar and other preventive measures can be used to avoid water inrush or reduce the losses caused. Coal mine water disaster emergency warning system can forecast water inrush, reduce the frequency of occurrence of water inrush, reduce coal mine casualties, improve the economic efficiency of enterprises and the government's destination image in the public heart. So it has high economic and social benefits. Currently, less coal mine water disaster emergency warning system is capable of practical application in the enterprise, this study most remain in the realm of theory, applicability needs to improve further.
This paper puts forward the view to design a water disaster emergency warning system for coal mine. It includes two important modules and three auxiliary modules. Two important modules are data monitoring and prediction, three auxiliary modules are user management, data query and after the information into. Firstly the monitoring indicators are built based on analysis of the main factors of mine water-related disasters, and the Access database and VB are used to design landing, data entry, query and the user management interface for coal mine.
Secondly, based on the comparative analysis on the conventional algorithm to predict coal mine burst water-related disasters, the BP neural network integrated model is selected, and the warning threshold value are determined according to the relationship between the maximum displacement of the water inrush and mine coal burst water-related disasters. The forecasts and ex post information input interface are designed by matlab, Access database and VB.
Finally, the Pingdingshan X coal is selected to be a sample for the paper. Data of four monitoring points is enter into the early warning system, and the appropriate measures are made in accordance with the output of the early warning system, to verify the operability and suitability for the system. The system can be used to monitor the possibility of water inrush, nip water inrush, reduce the enterprise safety production costs, and improve the economic and social benefits.
本文提出煤矿突发水灾害预警系统的设计,其主要包括数据监测和预测两个重要模块和用户管理、数据查询、事后信息录入三个辅助模块。文章首先以煤矿突发水灾害机理为基础,分析突水的主要影响因素,建立煤矿突发水灾害预警系统的监测指标体系,并运用Access数据库、VB,设计煤矿突发水灾害预警系统的登陆、数据输入、查询与用户管理界面。
其次通过对煤矿突发水灾害常规算法的对比分析,选择BP神经网络集成模型建立煤矿突发水灾害预测模型,并根据突水量与矿井最大排水量间的关系,对煤矿突发水灾害进行等级划分,确定预警界限值,将matlab、Access数据库和VB相结合,设计煤矿突发水灾害预警系统的预测、预报和事后信息录入界面。
最后通过对平顶山X.煤矿考察和监测,选取该矿4个点作为监测点,将数据输入预警系统,根据预警系统的输出做出相应措施,验证了煤矿突发水灾害系统的可操作性与适用性，能够为企业监测突发水灾害可能性,将突发水灾害事故扼杀于萌芽,降低事故发生频率和企业安全生产成本,提高企业的经济和社会效益。
With the rapid development of China's economy, growing demand for coal and increasing coal production task, the safety problem of coal mine has become particularly prominent. In recent years, the death toll of China's coal mine accident has been ranked first in the world, not only the basis of safety facilities are inadequate for China's coal mine, and staff safety awareness is poor, but also our early warning of coal mine safety management is carried out with a slow pace. The accident rescue has unfavorable factors such as the extent of the damage, emergency rescue difficulties, because of Geographical characteristics of the coal. But it is different from other coal mine accidents, if the water disaster of coal mine can be predicted in advance, water drainage, setting aside coal pillar and other preventive measures can be used to avoid water inrush or reduce the losses caused. Coal mine water disaster emergency warning system can forecast water inrush, reduce the frequency of occurrence of water inrush, reduce coal mine casualties, improve the economic efficiency of enterprises and the government's destination image in the public heart. So it has high economic and social benefits. Currently, less coal mine water disaster emergency warning system is capable of practical application in the enterprise, this study most remain in the realm of theory, applicability needs to improve further.
This paper puts forward the view to design a water disaster emergency warning system for coal mine. It includes two important modules and three auxiliary modules. Two important modules are data monitoring and prediction, three auxiliary modules are user management, data query and after the information into. Firstly the monitoring indicators are built based on analysis of the main factors of mine water-related disasters, and the Access database and VB are used to design landing, data entry, query and the user management interface for coal mine.
Secondly, based on the comparative analysis on the conventional algorithm to predict coal mine burst water-related disasters, the BP neural network integrated model is selected, and the warning threshold value are determined according to the relationship between the maximum displacement of the water inrush and mine coal burst water-related disasters. The forecasts and ex post information input interface are designed by matlab, Access database and VB.
Finally, the Pingdingshan X coal is selected to be a sample for the paper. Data of four monitoring points is enter into the early warning system, and the appropriate measures are made in accordance with the output of the early warning system, to verify the operability and suitability for the system. The system can be used to monitor the possibility of water inrush, nip water inrush, reduce the enterprise safety production costs, and improve the economic and social benefits.
引文
[1]董翠英,煤与瓦斯突出事故预警系统的研究[J].煤炭技术,2012,31(7)：85-86
[2]邢冬梅,叶义成,赵雯雯.我国矿山透水事故的统计分析及安全管理对策[J].金属矿山,2010,6：178-181
[3]董书宁,虎维岳.中国煤矿水灾害基本特征及其主要影响因素[J].煤田地质与勘探,2007,32(5)：34-37
[4]张志强.基于系统动力学的煤矿水灾害致因机理及安全评价研究[D].郑州：郑州大学.2011
[5]闫以朋.矿井水害的防治[J].煤炭技术,2010,29(3)：135-137
[6]陈佩佩,刘秀娥.矿井顶板突水预警系统研究与应用[J].煤炭科学技术,2010,38(12)：93-96
[7]王经明,董书宁.煤矿突水灾害的预警原理及其应用[J].煤田地质与勘探，2005,33(S0)：1-4
[8]齐怀琴,张松,王晗.基于MSP430F5438的超低功耗森林火灾预警系统设计[J].监控技术,2013,32(1)：28-32
[9]陈明.桥梁预警系统的数据预处理[J].上海交通大学学报,2012，46(10)：1680-1685
[10]中国煤炭地质总局一二九勘探队.十三矿矿井地质报告.2010
[11]张立海,张业成.中国煤矿突水灾害特点与发生条件[J].中国矿业.2008,17(2)：44-46
[12]闫志刚,白海波,张海荣.一种新型的矿井突水分析与预测的支持向量机模型[J].中国安全科学学报.2008,18(7)：166-170
[13]李加祥.用模糊数学预测煤层底板的突水[J].山东矿业学院学报,2010(1)：5-10
[14]白玉杰.煤矿水害原因分析及防治技术[J].煤炭技术.2009,28(11)：85-86
[15]李凯,茅献彪,李明等.含水层水压对底板断层突水危险性的影响[J].矿业安全与环保,2011,38(3)：1-4
[16]徐建文,石伟良,王飞等.矿井突水综合防治技术[J].煤矿开采,2010,15(4)：112-114
[17]常明辉,杨志斌等.矿井突水的预测预报[J].煤炭技术,2010.29(9)：113-116
[18]雷西玲,张景,谢天保.基于遗传神经网络的煤矿突水预测[J].计算机工程,2003(11)：132-134
[19]毛红川,刘志,邓春涛等.煤矿突水预测方法探讨[J].河北工业科技,2008,25(4)：196-199
[20]张春雷,钱家忠,赵卫东等.Bayes方法在矿井突水水源判别中的应用[J].煤田地质与勘探,2010,38(4)：34-37
[21]杨海军,王广才.煤矿突水水源判别与水量预测方法综述[J].煤田地质与勘探,2012,40(3)：48-54
[22]魏军,题正义.灰色聚类评估在煤矿突水预测中的应用[J].辽宁工程技术大学学报,2006(25)：44-46
[23]李春华,李春静.GA优化GNNM(1,1)的煤矿涌水量预测[J].水电能源科学,2011,29(2)：25-27
[24]Hansen L K, Salamon P. Neural network ensembles [J]. IEEE Trans Pattern Analysis and Machine Intelligence,1990,12(10):993-1001
[25]牛大鹏,王福利,何大阔.基于神经网络集成的诺西肽分批发酵过程混合建模[J].计量学报.2010,3 1(4)：364-368
[26]周志华,陈世福.神经网络集成[J].计算机学报,2002,25(1)：1-8
[27]傅向华,冯博琴,马兆丰,何明.增量构造负相关异构神经网络集成的方法[J].西安交通大学学报,2004,38(8)：796-799
[28]辛菊琴,蒋艳,舒少龙.综合用户偏好模型和BP神经网络的个性化推荐[J].计算机工程与应用,2013，49(2)：57-60
[29]韩立群.人工神经网络教程[M].北京：北京邮电大学出版社,2006：58-80
[30]张德丰.Matlab神经网络编程[M].北京：化学工业出版社,2011：131-156
[31]周纪芗,茆诗松.质量管理统计方法(第二版)[M].北京：中国统计出版社,2008：196-220
[32]ChristopherM, Bishop. Pattern RecognitionandMachineLearning[M]. Spirnger,2006
[33]Gelay Barbarosoglu, Arda Y. A Two-stage Stochastic Programming Framework for Transportation Planning in Disaster Response[J]. Journal of Operational Research Society, 2004(55):43-53
[34]Wybo J. L. Command centers and emergency management support[J]. Safety Science, 1998(30):131-138
[35]Mei-Po Kwan, Jiyeong Lee. Emergency response after 9/11:the potential of real-time 3D GIS for quick emergency response in micro-spatial environments[J]. Computers, Environment and Urban Systems,2005(29):93-113
[36]李慧杰,张云中,胡盛等.平顶山煤田十三矿二1煤层厚度特征及山西组聚煤规律探讨[J].中国煤炭地质,2011,23(8)：28-31
[37]平顶山天安煤业股份有限公司十三矿[J].中州煤炭,2010,7
[38]于辉光,郭德勇,吴建亭.平顶山十三矿突水特征与原因分析[J].煤矿安全与环保,2005,32(1)：1-3
[39]余本胜,王志鹏,马建宏.SQ-80/75B型无极绳绞车在复杂地质条件下的实践[J].煤炭工程,2010,10：56-58
[40]韩剑.平煤十三矿煤与瓦斯赋存规律与构造控制作用研究[C].焦作：河南理工大学安全科学与工程学院,2011：5-7
[41]樊晋豫,杨玉生,韩习运.平顶山十三矿中小构造分布规律与开采关系研究[J].煤炭科学技术,2002,30(12)：38-41
[42]于辉光,郭德勇,樊晋豫.平顶山十三矿突水灾害地质条件分析与研究[J].煤矿安全,2005,36(4)：24-25
[43]虎维岳,田干.我国煤矿水害类型及其防治对策[J].煤炭科学技术,2010,38(1)：92-96
[2]邢冬梅,叶义成,赵雯雯.我国矿山透水事故的统计分析及安全管理对策[J].金属矿山,2010,6：178-181
[3]董书宁,虎维岳.中国煤矿水灾害基本特征及其主要影响因素[J].煤田地质与勘探,2007,32(5)：34-37
[4]张志强.基于系统动力学的煤矿水灾害致因机理及安全评价研究[D].郑州：郑州大学.2011
[5]闫以朋.矿井水害的防治[J].煤炭技术,2010,29(3)：135-137
[6]陈佩佩,刘秀娥.矿井顶板突水预警系统研究与应用[J].煤炭科学技术,2010,38(12)：93-96
[7]王经明,董书宁.煤矿突水灾害的预警原理及其应用[J].煤田地质与勘探，2005,33(S0)：1-4
[8]齐怀琴,张松,王晗.基于MSP430F5438的超低功耗森林火灾预警系统设计[J].监控技术,2013,32(1)：28-32
[9]陈明.桥梁预警系统的数据预处理[J].上海交通大学学报,2012，46(10)：1680-1685
[10]中国煤炭地质总局一二九勘探队.十三矿矿井地质报告.2010
[11]张立海,张业成.中国煤矿突水灾害特点与发生条件[J].中国矿业.2008,17(2)：44-46
[12]闫志刚,白海波,张海荣.一种新型的矿井突水分析与预测的支持向量机模型[J].中国安全科学学报.2008,18(7)：166-170
[13]李加祥.用模糊数学预测煤层底板的突水[J].山东矿业学院学报,2010(1)：5-10
[14]白玉杰.煤矿水害原因分析及防治技术[J].煤炭技术.2009,28(11)：85-86
[15]李凯,茅献彪,李明等.含水层水压对底板断层突水危险性的影响[J].矿业安全与环保,2011,38(3)：1-4
[16]徐建文,石伟良,王飞等.矿井突水综合防治技术[J].煤矿开采,2010,15(4)：112-114
[17]常明辉,杨志斌等.矿井突水的预测预报[J].煤炭技术,2010.29(9)：113-116
[18]雷西玲,张景,谢天保.基于遗传神经网络的煤矿突水预测[J].计算机工程,2003(11)：132-134
[19]毛红川,刘志,邓春涛等.煤矿突水预测方法探讨[J].河北工业科技,2008,25(4)：196-199
[20]张春雷,钱家忠,赵卫东等.Bayes方法在矿井突水水源判别中的应用[J].煤田地质与勘探,2010,38(4)：34-37
[21]杨海军,王广才.煤矿突水水源判别与水量预测方法综述[J].煤田地质与勘探,2012,40(3)：48-54
[22]魏军,题正义.灰色聚类评估在煤矿突水预测中的应用[J].辽宁工程技术大学学报,2006(25)：44-46
[23]李春华,李春静.GA优化GNNM(1,1)的煤矿涌水量预测[J].水电能源科学,2011,29(2)：25-27
[24]Hansen L K, Salamon P. Neural network ensembles [J]. IEEE Trans Pattern Analysis and Machine Intelligence,1990,12(10):993-1001
[25]牛大鹏,王福利,何大阔.基于神经网络集成的诺西肽分批发酵过程混合建模[J].计量学报.2010,3 1(4)：364-368
[26]周志华,陈世福.神经网络集成[J].计算机学报,2002,25(1)：1-8
[27]傅向华,冯博琴,马兆丰,何明.增量构造负相关异构神经网络集成的方法[J].西安交通大学学报,2004,38(8)：796-799
[28]辛菊琴,蒋艳,舒少龙.综合用户偏好模型和BP神经网络的个性化推荐[J].计算机工程与应用,2013，49(2)：57-60
[29]韩立群.人工神经网络教程[M].北京：北京邮电大学出版社,2006：58-80
[30]张德丰.Matlab神经网络编程[M].北京：化学工业出版社,2011：131-156
[31]周纪芗,茆诗松.质量管理统计方法(第二版)[M].北京：中国统计出版社,2008：196-220
[32]ChristopherM, Bishop. Pattern RecognitionandMachineLearning[M]. Spirnger,2006
[33]Gelay Barbarosoglu, Arda Y. A Two-stage Stochastic Programming Framework for Transportation Planning in Disaster Response[J]. Journal of Operational Research Society, 2004(55):43-53
[34]Wybo J. L. Command centers and emergency management support[J]. Safety Science, 1998(30):131-138
[35]Mei-Po Kwan, Jiyeong Lee. Emergency response after 9/11:the potential of real-time 3D GIS for quick emergency response in micro-spatial environments[J]. Computers, Environment and Urban Systems,2005(29):93-113
[36]李慧杰,张云中,胡盛等.平顶山煤田十三矿二1煤层厚度特征及山西组聚煤规律探讨[J].中国煤炭地质,2011,23(8)：28-31
[37]平顶山天安煤业股份有限公司十三矿[J].中州煤炭,2010,7
[38]于辉光,郭德勇,吴建亭.平顶山十三矿突水特征与原因分析[J].煤矿安全与环保,2005,32(1)：1-3
[39]余本胜,王志鹏,马建宏.SQ-80/75B型无极绳绞车在复杂地质条件下的实践[J].煤炭工程,2010,10：56-58
[40]韩剑.平煤十三矿煤与瓦斯赋存规律与构造控制作用研究[C].焦作：河南理工大学安全科学与工程学院,2011：5-7
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