矿井局部通风设备故障诊断信息系统研究
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摘要
矿井局部通风设备系统故障是导致掘进工作面较易发生瓦斯爆炸事故的主要原因之一。矿井局部通风设备系统包含了多个组成部分,涉及的故障原因和种类较多。工作人员由于缺乏可以依赖的故障诊断信息,无法及时对所发生的故障进行准确和快速地分析判断,延长了停风时间,为瓦斯爆炸事故的发生创造了条件。因此,本文设计了一种基于事例和规则相结合的矿井局部通风设备故障诊断信息系统,并对相应原型系统的建模过程和软件进行开发和研究。
本文首先对矿井局部通风设备系统各组成单元故障进行收集和分析,建立系统故障诊断模型树,确定了关键故障单元;其次对故障信息表达方式和数据库建立等关键技术进行分析和研究,利用项目已完成的关键故障征兆和遗传算法规则获取软件得到故障诊断规则,采用SQL语言建立了矿井局部通风设备故障诊断信息系统的信息库;最后对系统建立的方法、总体结构及实现机制等进行分析和研究,采用IDSS建立了矿井局部通风设备故障诊断信息系统的功能模块体系结构,采用面向对象技术及UML建模语言对原型系统开发进行分析和建模,采用JAVA语言及JBuilder集成工具对系统原型软件进行开发,并利用煤矿故障实例进行了初步应用示范。
论文提出的事例和规则相结合的故障诊断方法,在矿井局部通风设备故障诊断领域是一次新的尝试和探索,首次以粗糙集理论和遗传算法相结合的方法对矿井局部通风设备故障诊断规则进行提取,研究为矿井局部通风设备故障诊断提供了信息支持,同时也提供了一种新的方法思路和原型软件工具,协助煤矿技术人员进行快速、准确故障诊断,对减少瓦斯爆炸事故发生以及提高煤矿安全管理具有积极意义。
The fault of in coal mine is one of the main reasons to induce most gas explosion accident occurred in heading face. The local ventilation equipment system comprise a number of equipments and components, which involve many fault types and causes. Because it is not enough the fault diagnosis information and appropriate approach to help the miner estimating the fault causes quickly and accurately. The ventilation break time without plan was extended and the gas is easy to overrun the standard limit, which bring a hidden trouble of gas explosion. Therefore, a fault diagnosis information system base on the incorporating the fault instances and corresponding rules is designed, and a prototype system is developed in this dissertation.
Firstly, the lots of fault of equipments and components units of local ventilation equipment system are collected and analyzed, the fault diagnosis tree model of system function unit are developed, the core fault units are confirmed in this dissertation. Secondly, the main technology of describing fault information and developing information base are analyzed and studied. Be use of the prototype programs of the key fault symptom and fault diagnosis rule acquiring algorithms to obtain fault diagnosis rules, the SQL language is used to develop the information base of local ventilation equipment in coal mine. Lastly, the develop method, architecture, realization mechanism of system are analyzed and studied. IDSS is adopted to construct the architecture of fault diagnosis information system. The prototype system is analyzed and modeled by the object-oriented technology (OOT) and UML, and the prototype system software are developed by the JAVA language and JBuilder tool, finally an instance demonstration research is performed.
It is a new method research that the combined of fault instances and rules of local ventilation equipment in coal mine in the dissertation. The approach of incorporating rough set theory and GA is used to obtain fault diagnosis rules of fault diagnosis information system. The achievements obtained in this research provide enough information to help the miner estimating the fault causes quickly and accurately, at the same time, it provide a new method, idea and a prototype system software tools to fault diagnosis of local ventilation equipment in coal mine, and it also is significant to decrease gas exploding accident and improve safety manage in coal mine.
本文首先对矿井局部通风设备系统各组成单元故障进行收集和分析,建立系统故障诊断模型树,确定了关键故障单元;其次对故障信息表达方式和数据库建立等关键技术进行分析和研究,利用项目已完成的关键故障征兆和遗传算法规则获取软件得到故障诊断规则,采用SQL语言建立了矿井局部通风设备故障诊断信息系统的信息库;最后对系统建立的方法、总体结构及实现机制等进行分析和研究,采用IDSS建立了矿井局部通风设备故障诊断信息系统的功能模块体系结构,采用面向对象技术及UML建模语言对原型系统开发进行分析和建模,采用JAVA语言及JBuilder集成工具对系统原型软件进行开发,并利用煤矿故障实例进行了初步应用示范。
论文提出的事例和规则相结合的故障诊断方法,在矿井局部通风设备故障诊断领域是一次新的尝试和探索,首次以粗糙集理论和遗传算法相结合的方法对矿井局部通风设备故障诊断规则进行提取,研究为矿井局部通风设备故障诊断提供了信息支持,同时也提供了一种新的方法思路和原型软件工具,协助煤矿技术人员进行快速、准确故障诊断,对减少瓦斯爆炸事故发生以及提高煤矿安全管理具有积极意义。
The fault of in coal mine is one of the main reasons to induce most gas explosion accident occurred in heading face. The local ventilation equipment system comprise a number of equipments and components, which involve many fault types and causes. Because it is not enough the fault diagnosis information and appropriate approach to help the miner estimating the fault causes quickly and accurately. The ventilation break time without plan was extended and the gas is easy to overrun the standard limit, which bring a hidden trouble of gas explosion. Therefore, a fault diagnosis information system base on the incorporating the fault instances and corresponding rules is designed, and a prototype system is developed in this dissertation.
Firstly, the lots of fault of equipments and components units of local ventilation equipment system are collected and analyzed, the fault diagnosis tree model of system function unit are developed, the core fault units are confirmed in this dissertation. Secondly, the main technology of describing fault information and developing information base are analyzed and studied. Be use of the prototype programs of the key fault symptom and fault diagnosis rule acquiring algorithms to obtain fault diagnosis rules, the SQL language is used to develop the information base of local ventilation equipment in coal mine. Lastly, the develop method, architecture, realization mechanism of system are analyzed and studied. IDSS is adopted to construct the architecture of fault diagnosis information system. The prototype system is analyzed and modeled by the object-oriented technology (OOT) and UML, and the prototype system software are developed by the JAVA language and JBuilder tool, finally an instance demonstration research is performed.
It is a new method research that the combined of fault instances and rules of local ventilation equipment in coal mine in the dissertation. The approach of incorporating rough set theory and GA is used to obtain fault diagnosis rules of fault diagnosis information system. The achievements obtained in this research provide enough information to help the miner estimating the fault causes quickly and accurately, at the same time, it provide a new method, idea and a prototype system software tools to fault diagnosis of local ventilation equipment in coal mine, and it also is significant to decrease gas exploding accident and improve safety manage in coal mine.
引文
[1] 赵书田.黑龙江省煤矿通风安全隐患分析与重大瓦斯煤尘和火灾事故预防对策. 煤炭技术,2002, 21(10): 1-5.
[2] http://www.hnsafety.gov.cn.
[3] 章跃平,张宁.基于铁路设备故障诊断专家系统研究——模糊推理原型分析.中国科技信息,2006(8): 319-320.
[4] 黄开启,刘晓波.基于数据库的多征兆模糊故障诊断专家系统的研究.风机技术, 2004(3): 43-46.
[5] Gong X Y, Xue H, Tao X L et al. Research on Fault diagnosis System of Local Ventilation Equipment in Coal Mine Based on Multidisciplinary Technology Chinese Journal of Mining Sciences and Technology, 2006(9): 317-320.
[6] Har dcastleSG.. Electronic vane anemometry finding a suitable replacement of mechanical analog devices for mine airflow assessment. Proceedings of the 5th US Mine Ventilation Symposium, 1991(3): 23-35.
[7] Har dcastleSG.. Testing stench gas emergency warning systems with an odourless surrogate gas. Journal of the Mine Ventilation Society of South Africa, 2001, 54(2): 15-21.
[8] Mironowicz W. Hazard monitoring and control system of ventilation in a hard coal mine. Proceedings of the 1998 International Symposium on Safety Science and Technology, 1998(9): 41-48.
[9] Hu Y N, Olga I K, Miroslav KN. onlinear control of mine ventilation networks. Systems & Control Letters, 2003,49(10): 239-254 .
[10] Torano A R, Rodryguez D A, Cuesta G. A computer program for calculating ventilation in tunneling works based on an explicit method. Oiedo University, 2002(6):12-16.
[11] Star W X.,Ertugrul T. Analysis of Mine Ventilation Systems Using Operations Research Methods. Mine Ventilation Systems, 1998(5): 245-254.
[12] Ian SL, AmandaJC, YangZY. The ventilation and climate modelling of rapid development tunnel drivages. University of Nottingham, 2003.
[13] 华 臻. 虚拟现实技术在矿井通风系统中的应用. 煤炭科学技术,2004(3): 44-48.
[14] 杨庆学. 大型地下洞室群施工通风动态仿真研究. 水电站设计,2003(1): 1-5.
[15] 高新春. 通风安全状况评估. 矿业安全与环保,2002,29(5): 23-26.
[16] 臧小杰. 模糊控制理论在煤矿通风安全自动化系统中的应用. 中国安全科学学报,2000, 10(3): 33-37.
[17] Shen L X, Francis E.H, Qu L S, et al. Fault diagnosis using Rough Sets Theory, Computers in Industry, 2000, 43: 61-72.
[18] Burrell P, Inman D. An expert system for the analysis of faults in an electricity supply network. problems and achievements. Computers in Industry, 1998, 37:113-123.
[19] Karpenko M, Sepehria N, Scuse D. Diagnosis of process valve actuator faults using a multilayer neural network. Control Engineering Practice,2002(11): 1289-1299.
[20] Wakulicz D, Alicja. Applying rough set theory to multi stage medical diagnosing Fundament a Information, 2003(3): 387-408.
[21] 李浩.基于粗糙集理论的水轮机计算机调速系统故障诊断的研究:[学位论文].武汉:武汉理工大学,2002.
[22] 王卫平. 基于粗糙集的数控机床故障诊断最小化方法. 组合机床与自动化加工技术.2001(2):31-35.
[23] 项新建. 基于粗糙集理论的电力变压器故障诊断研究. 仪器仪表学报, 2003(6): 568-571.
[24] 陆春月,王俊元. 机械故障诊断的现状及发展趋势. 机械管理开发, 2004(12): 85-86.
[25] 黄伟力,黄伟建,王飞等. 机械设备故障诊断技术及其发展趋势. 矿山机械, 2005(1): 66-68.
[26] 屈梁生,何正嘉. 机械故障诊断学. 上海:上海科学技术出版社, 1986.
[27] 黄志坚, 裘丽华. 对现代机械故障诊断技术方法论的探讨. 科学技术与辩证法,2001(6): 26-29.
[28] 刘建功, 李凤锦, 赵振山. 煤矿电工实用手册. 北京:兵器工业出版社,1993.
[29] 王翔, 李伯全. 机械产品智能化故障诊断技术研究现状与展望.机械,2002(2): 1-3.
[30] 谢锡纯,李晓. 矿山机械与设备. 江苏:中国矿业大学出版社,2000.
[31] 刘用中,段浩钧. 煤矿电工学. 北京:煤炭工业出版社,1984.
[32] 李咸华. 高瓦斯矿井掘进工作面局部通风机供电线路改造. 煤矿安全,2004(7): 33-35.
[33] 王永安. 局部通风机排放瓦斯方法与安全性的探讨. 山西煤炭,2003(9): 24-25.
[34] 崔岗,陈开岩.矿井通风系统安全可靠性综合评价方法探讨.煤炭科学技术,1999,27(12): 40-43.
[35] 李世华,向健. 矿井通风设备使用维修. 北京:机械工业出版社,1990.
[36] 龚晓燕. 矿井局部通风系统可靠性评估和提高措施:[学位论文]. 西安:西安矿业学院,1993.
[37] 张凤琴. 数据库原理及应用. 北京:清华大学出版社,2005.
[38] 闪四清. SQL Server 2000 实用教程. 北京:人民邮电出版社,2000.
[39] 杨正洪,郑齐健,孙延辉. 中文 SQL Server 2000 关系数据库系统管理与开发指南.北京:机械工业出版社,2001.
[40] 蒋晓健,郑力,梁宇澜. 基于 SQL SERVER 的面向对象数据库的构建.计算机工程与应用,2004(4): 178-181.
[41] 启明工作室. MIS 系统开发与应用. 北京:人民邮电出版社, 2005.
[42] 姜旭平,姚爱群. 信息系统开发方法. 北京: 清华大学出版社, 2004.
[43] Cai Z M, Hong G X, Shao P, et al. A new Approach to Intrusion Detection Based on Rough Set Theory. Chinese Journal of Computers, 2003, 26(3): 361-366.
[44] Zhai L Y. Feature extraction using rough set theory and genetic algorithms-an application for the simplification of product quality evaluation. Computers & Industrial Engineering, 2002, 43(5): 661-676.
[45] 李虎,赵龙刚. UML 基础、案例与应用. 北京:人民邮电出版社,2004.
[46] 王林,高国安. 面向对象的IDSS模型库系统的构造.电脑与信息技术,2000(1): 11-17.
[47] 张维明,刘忠,肖卫东等. 信息系统建模. 北京:电子工业出版社,2002.
[48] 刘宴虎.系统分析与软件开发过程管理实用案例教程.北京:清华大学出版社,2003.
[49] 黄明,梁旭. Java 信息系统设计与开发实例. 北京:机械工业出版社,2004.
[2] http://www.hnsafety.gov.cn.
[3] 章跃平,张宁.基于铁路设备故障诊断专家系统研究——模糊推理原型分析.中国科技信息,2006(8): 319-320.
[4] 黄开启,刘晓波.基于数据库的多征兆模糊故障诊断专家系统的研究.风机技术, 2004(3): 43-46.
[5] Gong X Y, Xue H, Tao X L et al. Research on Fault diagnosis System of Local Ventilation Equipment in Coal Mine Based on Multidisciplinary Technology Chinese Journal of Mining Sciences and Technology, 2006(9): 317-320.
[6] Har dcastleSG.. Electronic vane anemometry finding a suitable replacement of mechanical analog devices for mine airflow assessment. Proceedings of the 5th US Mine Ventilation Symposium, 1991(3): 23-35.
[7] Har dcastleSG.. Testing stench gas emergency warning systems with an odourless surrogate gas. Journal of the Mine Ventilation Society of South Africa, 2001, 54(2): 15-21.
[8] Mironowicz W. Hazard monitoring and control system of ventilation in a hard coal mine. Proceedings of the 1998 International Symposium on Safety Science and Technology, 1998(9): 41-48.
[9] Hu Y N, Olga I K, Miroslav KN. onlinear control of mine ventilation networks. Systems & Control Letters, 2003,49(10): 239-254 .
[10] Torano A R, Rodryguez D A, Cuesta G. A computer program for calculating ventilation in tunneling works based on an explicit method. Oiedo University, 2002(6):12-16.
[11] Star W X.,Ertugrul T. Analysis of Mine Ventilation Systems Using Operations Research Methods. Mine Ventilation Systems, 1998(5): 245-254.
[12] Ian SL, AmandaJC, YangZY. The ventilation and climate modelling of rapid development tunnel drivages. University of Nottingham, 2003.
[13] 华 臻. 虚拟现实技术在矿井通风系统中的应用. 煤炭科学技术,2004(3): 44-48.
[14] 杨庆学. 大型地下洞室群施工通风动态仿真研究. 水电站设计,2003(1): 1-5.
[15] 高新春. 通风安全状况评估. 矿业安全与环保,2002,29(5): 23-26.
[16] 臧小杰. 模糊控制理论在煤矿通风安全自动化系统中的应用. 中国安全科学学报,2000, 10(3): 33-37.
[17] Shen L X, Francis E.H, Qu L S, et al. Fault diagnosis using Rough Sets Theory, Computers in Industry, 2000, 43: 61-72.
[18] Burrell P, Inman D. An expert system for the analysis of faults in an electricity supply network. problems and achievements. Computers in Industry, 1998, 37:113-123.
[19] Karpenko M, Sepehria N, Scuse D. Diagnosis of process valve actuator faults using a multilayer neural network. Control Engineering Practice,2002(11): 1289-1299.
[20] Wakulicz D, Alicja. Applying rough set theory to multi stage medical diagnosing Fundament a Information, 2003(3): 387-408.
[21] 李浩.基于粗糙集理论的水轮机计算机调速系统故障诊断的研究:[学位论文].武汉:武汉理工大学,2002.
[22] 王卫平. 基于粗糙集的数控机床故障诊断最小化方法. 组合机床与自动化加工技术.2001(2):31-35.
[23] 项新建. 基于粗糙集理论的电力变压器故障诊断研究. 仪器仪表学报, 2003(6): 568-571.
[24] 陆春月,王俊元. 机械故障诊断的现状及发展趋势. 机械管理开发, 2004(12): 85-86.
[25] 黄伟力,黄伟建,王飞等. 机械设备故障诊断技术及其发展趋势. 矿山机械, 2005(1): 66-68.
[26] 屈梁生,何正嘉. 机械故障诊断学. 上海:上海科学技术出版社, 1986.
[27] 黄志坚, 裘丽华. 对现代机械故障诊断技术方法论的探讨. 科学技术与辩证法,2001(6): 26-29.
[28] 刘建功, 李凤锦, 赵振山. 煤矿电工实用手册. 北京:兵器工业出版社,1993.
[29] 王翔, 李伯全. 机械产品智能化故障诊断技术研究现状与展望.机械,2002(2): 1-3.
[30] 谢锡纯,李晓. 矿山机械与设备. 江苏:中国矿业大学出版社,2000.
[31] 刘用中,段浩钧. 煤矿电工学. 北京:煤炭工业出版社,1984.
[32] 李咸华. 高瓦斯矿井掘进工作面局部通风机供电线路改造. 煤矿安全,2004(7): 33-35.
[33] 王永安. 局部通风机排放瓦斯方法与安全性的探讨. 山西煤炭,2003(9): 24-25.
[34] 崔岗,陈开岩.矿井通风系统安全可靠性综合评价方法探讨.煤炭科学技术,1999,27(12): 40-43.
[35] 李世华,向健. 矿井通风设备使用维修. 北京:机械工业出版社,1990.
[36] 龚晓燕. 矿井局部通风系统可靠性评估和提高措施:[学位论文]. 西安:西安矿业学院,1993.
[37] 张凤琴. 数据库原理及应用. 北京:清华大学出版社,2005.
[38] 闪四清. SQL Server 2000 实用教程. 北京:人民邮电出版社,2000.
[39] 杨正洪,郑齐健,孙延辉. 中文 SQL Server 2000 关系数据库系统管理与开发指南.北京:机械工业出版社,2001.
[40] 蒋晓健,郑力,梁宇澜. 基于 SQL SERVER 的面向对象数据库的构建.计算机工程与应用,2004(4): 178-181.
[41] 启明工作室. MIS 系统开发与应用. 北京:人民邮电出版社, 2005.
[42] 姜旭平,姚爱群. 信息系统开发方法. 北京: 清华大学出版社, 2004.
[43] Cai Z M, Hong G X, Shao P, et al. A new Approach to Intrusion Detection Based on Rough Set Theory. Chinese Journal of Computers, 2003, 26(3): 361-366.
[44] Zhai L Y. Feature extraction using rough set theory and genetic algorithms-an application for the simplification of product quality evaluation. Computers & Industrial Engineering, 2002, 43(5): 661-676.
[45] 李虎,赵龙刚. UML 基础、案例与应用. 北京:人民邮电出版社,2004.
[46] 王林,高国安. 面向对象的IDSS模型库系统的构造.电脑与信息技术,2000(1): 11-17.
[47] 张维明,刘忠,肖卫东等. 信息系统建模. 北京:电子工业出版社,2002.
[48] 刘宴虎.系统分析与软件开发过程管理实用案例教程.北京:清华大学出版社,2003.
[49] 黄明,梁旭. Java 信息系统设计与开发实例. 北京:机械工业出版社,2004.