【作者】 李琨；

【导师】 杨斌； 张云生；

【作者基本信息】 昆明理工大学 ， 冶金工程控制， 2009， 博士

【摘要】 煤炭是世界上储量最多、分布最广的常规能源,也是重要的战略资源,在冶金、电力、化工等领域广泛应用,未来100年内仍将是一种主要能源和战略资源。煤炭在冶金行业有重要的作用,炼焦用煤、喷吹和烧结用煤、以及用于发电、锅炉等的动力煤是冶金生产的重要保证。我国煤矿开采的煤层瓦斯含量大、煤层透气性低,在开采前抽放瓦斯很不容易,高瓦斯矿井占多数。在采掘中,瓦斯容易放散,在一定的条件下会产生煤尘和瓦斯的突出现象,形成瓦斯爆炸事故。煤矿瓦斯灾害的防治是我国煤炭工业发展亟待解决的重大问题。由于地质条件、采动方式、人机环境的复杂性与相互作用,现有研究无法清楚地表达灾害发生的机理和作用规律,也没有成熟的预警理论、检测技术和避免管理与行为失误的有效方法。“对瓦斯灾害发生机理认识不清”是国家安全生产主管部门、科技主管部门及产业界的共识。在此情况下,本文的工作目标是：转变目前的研究视角,从系统科学的角度,对煤矿瓦斯灾变的因素和过程进行综合分析,研究瓦斯灾变模型,设计瓦斯监控系统的事故预测算法,同时解决现有瓦斯监控系统的可靠性、,实时性、准确性不高的关键性技术问题,研制新型煤矿瓦斯监控设备,新型主要指具有瓦斯灾变预测的功能。本文采用的研究方法是：用整体建模的方法,把煤矿生产系统看成是由人员、机械、地质环境相互作用的复杂系统,应用复杂系统理论的涌现性特性分析瓦斯灾变主体,建立灾变模型；同时应用综合集成法根据煤矿的现场条件与生产环境,对嵌入式技术、数字图象技术、实时数据库技术、软件滤波技术、和神经网络技术进行融合,研究开发带预警模型和抗干扰的实时操作系统+嵌入式处理器+嵌入式数据库的专用设备,从系统分析的角度来解决瓦斯灾变机理认识不清的理论问题,从工程应用的角度来解决可靠性、实时性、信号滤波的前端的现场技术问题,即一个瓦斯灾变的理论问题和三个设备缺陷的技术问题。复杂系统的整体涌现性是指系统整体才具有,孤立的部分及其总和不具有的特性。本文发现煤矿现场的各灾变因子大多是耦合相关的,通过分析发现因子间存在着关系环,属于复杂系统,因此其动力学演化会呈现出复杂系统的涌现性特征,应用布尔自动器网络推演出系统的状态演化图,得出两个点吸引子和两个周期吸引子,可作为安全评价与灾变预警模型,最后通过事故报告与数据,来验证模型可靠性,用复杂系统理论对瓦斯风险评价和事故预警进行一些探讨和研究。这是在目前瓦斯灾害发生机理认识不清的情况下的一次尝试,是首次应用复杂系统理论对瓦斯灾害防治进行研究。因此煤矿瓦斯灾变模型是本文的主要理论成果,应用复杂性理论的涌现性特性来进行整体建模是本文的主要理论创新点。研究中解决的三个技术问题：1、基于“灰箱”模型的瓦斯“冒大数”的滤波器模型：分析瓦斯检测中出现的大数的原因,通过实验判断和总结瓦斯浓度中脉冲干扰的规律,对训练样本进行处理；用系统辨识的方法,通过BP神经网络建立适合“大数”滤波的“黑箱”模型；通过训练和测试对滤波器进行验证分析,建立“灰箱”滤波模型。“灰箱”滤波模型的建立提高了瓦斯检测中对大数的滤除,减少了误报警和漏报警；2、基于BerkeleyDB的嵌入式瓦斯实时数据库：根据Berkeley DB的技术特性,研究针对煤矿瓦斯信号的数据采集方法、数据库KEY/DATA对存储方案及实时/历史传感器数据的数据库查询策略,开发用于煤矿瓦斯监控系统的嵌入式数据库,实现窗口登录、数据采集、系统界面、数据库存储、实时/历史数据查询、实时曲线显示等功能模块,得到了专用瓦斯数据库；3、基于μCOS-Ⅱ的瓦斯图形监控终端：应用实时操作系统μC/OS-Ⅱ的特性,根据煤矿现场的瓦斯监控需要,通过平台的整合与移植、串行通信驱动程序开发、数据的解析与图形化显示等技术集成,设计完成基于嵌入式技术的煤矿专用的图形监控终端。瓦斯“大数”滤波器、瓦斯数据库、瓦斯监控终端是本文的三个技术成果,应用“灰箱”模型设计滤波器、应用Berkeley DB设计瓦斯数据库、应用μCOS-Ⅱ设计监控终端是本文的三个技术创新点。理论成果用于后端的核心算法,技术成果用于前端的数据处理,研制的新型煤矿瓦斯监控终端在陆东、大舍、马关等煤矿进行了应用,提高了瓦斯治理水平,杜绝了重大事故的发生。更多还原

【Abstract】 Coal with the world’s largest reserves and most widely distributed of conventional energy is also important strategic resources, widely used in areas such as metallurgical, power, chemicals. In the next 100 years, it will continue to be a major energy and strategic resource. Coal in the Metallurgical process assumes the important role. Coking coal, injecting and sintering coal, and steam coal, as well as power generation, boilers, etc. are the important guarantee for metallurgical production.China’s coal seam of coal mining full of gas, with low permeability, and gas drainage before the exploitation is not easy, high-gas coal mine majority. In mining, the gas emission easily, under certain conditions dust and gas will have a prominent phenomenon in the formation of gas explosion accident. Disaster prevention and treatment of coal in China’s coal industry in the development of major issues to be settled urgently. Due to geological conditions, mining methods, human-machine environment complexity and interaction, existing research can not clearly express the mechanism of disasters and the role of the law, nor a mature theory of early warning, detection techniques and avoid mistakes in the management and conduct effective methods. It is the consensus for production department in charge of national security, science and technology authorities and industry that understanding the mechanism of gas disasters happen nuclear.In this case, the objectives of this paper are:the changing perspective of the current study, from the perspective of system science, comprehensive analyzing elements and process of coal catastrophism, researching gas catastrophe model, designing the accident prediction algorithm of the gas monitoring system. At the same time, solve key technical problems of the existing gas monitoring system, such as reliability, real-time, and accuracy, development of new coal mine gas monitoring equipment, with gas disaster prediction function.In this paper, an approach to the study are:studying the overall modeling methodology, the coal mine production systems as human, mechanical, geological environment interactions of complex systems, application of emergence characteristics of complex systems theory, analyzes the agents of the gas disaster and establishes the catastrophe model. At the same time, the application of integrated method in accordance with the scene of mine conditions and production environment for embedded technology, digital image technology, real-time database technology, software filtering technology, and neural network technology for integration, research and development with early warning of real-time model and anti-jamming operating system+embedded processor+embedded database of specialized equipment. From the perspective of systems analysis to solve the understanding unclear questions of the gas disaster mechanism theory, from the perspective of engineering applications to solve the field technical problems, reliability, real-time signal filtering, namely one theory of a gas disaster problem, and three equipment technical defects.The emergence character of complex systems refers to the overall system as a whole can have, but to isolate parts and the sum of them do not have.This article was found that coal mine disaster factors, coupling, related by analyzing exist the relationship loops, and its dynamic evolution will show the emergence characteristics. By the Boolean Automata network can be deduced to the system state evolution map, drawn two point attractors and two cycle attractors that can be used for disaster early warning analysis and mine security assessment. Finally, incident reporting and data to verify the model reliability, is an attempt of the first application of complex systems theory to study for the gas disaster prevention. Thus coal catastrophe model is the main theoretical results of this paper. The application of complexity theory and the characteristics of the emergence of an overall modeling are the major theoretical innovation in this article point.There are three technical problems solved in study:1, the filter model of the gas "bubble large numbers" based on the "gray box" model:Analysis of reasons of gas detection appearing in large numbers, to determine through experiments and summarize the law of the gas concentration pulse interference, for processing the training samples; through BP neural network to establish of a suitable "black box" model for "large numbers" filter; through training and testing to verify and analyze the filter, to establish a "gray box" filter model. "Gray box" filter model to improve the gas detection of large numbers, the reduction of False Alarm and leakage alarm; 2, embedded gas real-time database:based on the Berkeley DB:According to the technical characteristics of Berkeley DB, research for coal mine gas signal data collection methods, database KEY/DATA storage solutions and real-time/the history of the database sensor data write/read strategy, develop the embedded database for coal mine gas monitoring system. The realization of the window registry, data acquisition, system interface, database storage, real-time/historical data search, real-time curve display function modules; 3, graphics gas monitoring Terminal based on theμCOS-Ⅱ:Application of real-time operating systemμC/OS-Ⅱfeatures, according to coal mine gas monitoring field needs, through the platform integration and transplantation, serial communication driver development, data analysis and graphics display technology integration, designed the graphics Coal Monitoring Terminal.Gas "large numbers" filter, the gas database, the gas monitoring terminal in this article are three technological achievements. Application of "gray box" model design the gas filter, application of Berkeley DB design the gas database, application ofμCOS-Ⅱdesign the gas terminal in this article are three technical innovation points. Theoretical results for the core back-end algorithm, and technological achievements for the front end data processing. The terminal application of coal mine on Ludong, Dashe, Maguan, etc., improved the level of the gas control, put an end to major accidents.更多还原