基于智能信息处理的煤矿瓦斯动态预测研究

发布时间：2018-06-18 08:14

本文选题：瓦斯涌出量 + 瓦斯浓度　；参考：《武汉理工大学》2015年博士论文

【摘要】：煤炭资源是重要的战略物资能源,其在国民经济发展中起到关键作用。在煤炭开采过程中,瓦斯灾害是十分常见的事故,造成了大量的人员伤亡和经济财产损失。为了提高瓦斯安全预测水平和降低瓦斯危害,瓦斯动态智能预测方法和模型的研究是十分必要的;基于此,主要目标是研究出适应度和预测精度更好的瓦斯动态预测方法。针对我国瓦斯灾害的高瓦斯涌出、瓦斯爆炸、煤与瓦斯突出等显著特点,结合智能信息处理技术,对瓦斯涌出量、瓦斯浓度、煤与瓦斯突出等方面的预测及分析方法进行了深入研究。研究主要包括以下几个方面的内容:1)分析了国内外瓦斯动态预测方法,讨论了瓦斯涌出量和瓦斯浓度的影响因素、煤与瓦斯突出机理及影响因素,确定了研究对象的预测方法分为数值计算和分类计算两个方向。通过分析瓦斯动态的不同特征,进一步拓展到展开数值计算预测算法、分类计算预测算法、信息生成算法和瓦斯动态预测模型研究。2)提出了对立度数值计算(Opposite Degree-Numerical Computation,OD-NC)算法和对立度分类计算(Opposite Degree-Classification Computation,OD-CC)算法。对立度相关算法基于语义对立度、神经网络、遗传算法、聚类分析等智能信息处理的相关概念和理论。OD-NC算法和OD-CC算法能够分别进行煤矿瓦斯动态的数值预测和分类预测。3)提出了信息生成(Information Generation,IG)算法。算法分为两个模板,即数值计算句型模板(Numerical Computation Sentence Template,NCST)和分类计算句型模板(Classification Computation Sentence Template,CCST);不同的句型模板可以生成不同的信息。IG算法可以和对立度相关算法进行对接,也可以和系统模型结合,并最终能生成相关信息。此外,IG算法还可以对部分瓦斯数据进行安全分析。4)研究了对立度相关算法和信息生成算法在瓦斯动态预测中的应用。研究包括:基于OD-NC和IG的瓦斯涌出量及瓦斯浓度预测,基于OD-CC和IG的煤与瓦斯突出及瓦斯安全状态预测;其中,瓦斯安全状态预测和瓦斯涌出量、瓦斯浓度、煤与瓦斯突出关系密切,其预测也是对算法预测和性能分析进行验证的重要手段。通过对比不同的智能算法预测的结果,验证了对立度相关算法在工程实例中的可行性和有效性;通过专家打分的方法,说明了信息生成算法在瓦斯预测中的评价效果。5)采用ASP.NET+C#+Access 2007实现了智能瓦斯预测模型。该模型结合安徽淮北矿业集团涡北煤矿的实际情况,基于对立度数值计算算法、信息生成算法的内容,并初步分析了其工作面风巷的瓦斯浓度的安全状态,与实际情况一致。因此,经过实例验证,进一步证明了该算法及模型的可靠性和智能性。总之,对立度数值计算算法、对立度分类计算算法的泛化能力和适应度较好、预测精度高;对立度相关算法和信息生成算法是可行且有效的。研究基于智能信息处理技术的瓦斯动态预测方法和模型对煤矿安全生产和监督具有积极作用;其预测方法和模型为预防和减少煤矿瓦斯灾害事故提供方案支持和理论参考。
[Abstract]:Coal resources are important strategic materials and energy, which play a key role in the development of national economy. In the process of coal mining, the gas disaster is a very common accident, resulting in a large number of casualties and economic property losses. In order to improve the prediction level of gas safety and reduce the damage of gas, the intelligent prediction method and model of gas dynamics are used. Based on this, the main objective is to study the gas dynamic prediction method with better adaptability and prediction accuracy. In view of the significant characteristics of gas emission, gas explosion, coal and gas outburst in China's gas disaster, the gas emission, gas concentration, coal and gas outburst are combined with intelligent information processing technology. The main contents are as follows: 1) the main contents are as follows: 1) the method of gas dynamic prediction at home and abroad is analyzed, the influence factors of gas emission and gas concentration, the mechanism of coal and gas outburst and the influencing factors are discussed, and the prediction methods of the research object are divided into numerical calculation and classification. Two directions are calculated. By analyzing the different characteristics of gas dynamics, the numerical calculation prediction algorithm, the classification and prediction algorithm, the information generation algorithm and the gas dynamic prediction model study.2 are further expanded, and the Opposite Degree-Numerical Computation (OD-NC) algorithm and the opposition classification calculation (Opp) are proposed. Osite Degree-Classification Computation, OD-CC) algorithm. Antithesis correlation algorithm based on semantic opposition degree, neural network, genetic algorithm, cluster analysis and other related concepts and theories,.OD-NC algorithm and OD-CC algorithm can carry out the numerical prediction and classification prediction of coal mine gas dynamics and classify the.3). The information generation (Inf) is proposed (Inf). Ormation Generation, IG) algorithm. The algorithm is divided into two templates, namely, the Numerical Computation Sentence Template, NCST, and the classification pattern template (Classification Computation Sentence Template). In addition, the IG algorithm can also carry out a safety analysis of some gas data. In addition, the IG algorithm can also carry out a safety analysis of some gas data.4) and study the application of the correlation algorithm and the information generation algorithm in the gas dynamic prediction. The research includes the gas emission and gas concentration prediction based on the OD-NC and IG, based on the O The prediction of coal and gas outburst and gas safety status of D-CC and IG, the prediction of gas safety state and gas emission, gas concentration, coal and gas outburst are closely related, and the prediction is also an important means to verify the prediction and performance analysis of the algorithm. The feasibility and effectiveness of the algorithm in the engineering example; through the method of expert scoring, it illustrates the evaluation effect of information generation algorithm in gas prediction.5) using ASP.NET+C#+Access 2007 to realize the intelligent gas prediction model. This model is based on the actual situation of the Anhui Huaibei Mining Group vorticity coal mine and based on the numerical calculation of the degree of opposites. The method, the content of the information generation algorithm, and the preliminary analysis of the safety state of the gas concentration in the wind tunnel of the working face, is consistent with the actual situation. Therefore, the reliability and intelligence of the algorithm and the model are further proved by example. In a word, the generalization ability and adaptability of the antithesis algorithm and the algorithm of opposition degree classification calculation are also proved. The method and model of gas dynamic prediction based on intelligent information processing technology have a positive effect on the safety production and supervision of coal mine. The prediction method and model provide the support and reason for the prevention and reduction of coal mine gas disaster accidents. On the reference.
【学位授予单位】：武汉理工大学
【学位级别】：博士
【学位授予年份】：2015
【分类号】：TD712

【参考文献】