基于物元分析的煤自燃动态预测研究

发布时间：2018-04-26 10:07

本文选题：煤自燃预测 + 物元分析　；参考：《太原理工大学》2017年硕士论文

【摘要】：长久以来,煤炭作为我国最主要最基础的能源,其消费量在一次能源消费总量中占到70%左右,绝对消费量依然在不断增加。然而,我国煤炭自燃现象存在于大约56%的国有重点煤矿中,威胁着矿井工人的生命安全,阻碍了煤矿生产效率的提高,严重影响了煤矿的安全生产。因此,很有必要对煤炭自燃现象进行深入研究,及早发现煤自燃的征兆,准确、及时、高效地做出预测预报,为矿井工人的生命安全保驾护航,提高煤矿的安全生产效益。本文在充分认识煤自燃灾害的严重性和煤自燃预测的重要意义的前提下,尝试将物元分析方法应用于煤自燃的动态预测中。首先对煤自燃的机理、研究现状、现有的煤自燃预测方法以及物元理论的应用现状进行了总结以及研究分析;在深入学习物元分析理论的基础上,论述了一些物元模型中使用到的物元的基本概念、处理数据的方法和构建物元模型的一般步骤;在西山23509工作面采集煤样后,通过对程序升温实验数据的分析,得到了煤自燃动态预测模型中的指标预测体系(O2、CO、CH4、CO2)和相对应的经典域与节域;在进一步对煤自燃动态预测模型的构建中,使用熵权法确定指标的权重值,避免了传统专家打分的过于主观性;通过对MATLAB的介绍与学习,完成了基于MATLAB对煤自燃动态预测的物元模型中复杂计算过程的实现,使计算过程简便,结果精确。在实例应用方面,选用西山官地煤矿23509工作面采空区的实时观测数据进行计算分析,再通过与实际情况进行对比,取得了良好的结果,证明了该方法在该煤矿煤自燃预测的可行性。由于煤自燃过程的复杂性,单一指标预测煤自燃的不全面性,运用本方法建立指标气体的综合指标预测体系,尽可能全面的考虑影响煤自燃预测的因素,使基于物元分析方法建立的煤自燃动态预测模型更具有科学性,预测结果更加可靠。通过实例分析证明了物元分析法在煤自燃预测中具有科学性和实用性,为煤自燃预测提供了一种新的思路和方法,对减轻和防止煤自燃具有重要意义。
[Abstract]:For a long time, as the most important and basic energy in China, coal consumption accounts for about 70% of the total primary energy consumption, and the absolute consumption is still increasing. However, the phenomenon of coal spontaneous combustion in China exists in about 56% of the key state-owned coal mines, which threatens the safety of mine workers, hinders the improvement of coal production efficiency and seriously affects the safety of coal production. Therefore, it is necessary to deeply study the phenomenon of spontaneous combustion of coal, find the signs of spontaneous combustion of coal as soon as possible, make accurate, timely and efficient prediction and forecast, protect the safety of mine workers and improve the benefit of safe production in coal mines. On the premise of fully understanding the severity of coal spontaneous combustion disaster and the important significance of coal spontaneous combustion prediction, this paper attempts to apply matter-element analysis method to the dynamic prediction of coal spontaneous combustion. First of all, the mechanism of coal spontaneous combustion, the present research situation, the existing prediction methods of coal spontaneous combustion and the application status of matter-element theory are summarized and analyzed, on the basis of in-depth study of matter-element analysis theory, The basic concept of matter-element used in matter-element model, the method of processing data and the general steps of constructing matter-element model are discussed. The index prediction system of coal spontaneous combustion dynamic prediction model (O2COCH4CO2) and the corresponding classical domain and segmental domain are obtained, and the weight value of the index is determined by entropy weight method in the further construction of the prediction model of coal spontaneous combustion performance. Through the introduction and study of MATLAB, the complex calculation process of matter element model based on MATLAB for predicting coal spontaneous combustion is completed, which makes the calculation process simple and accurate. In practical application, the real time observation data of goaf in 23509 face of Xishan Guandi Coal Mine are calculated and analyzed, and good results are obtained by comparing them with the actual situation. It is proved that this method is feasible in the prediction of coal spontaneous combustion in this coal mine. Because of the complexity of the coal spontaneous combustion process and the incomplete prediction of the coal spontaneous combustion with a single index, the comprehensive index prediction system of the index gas is established by using this method, and the factors affecting the prediction of the spontaneous combustion of the coal are considered as comprehensively as possible. It makes the prediction model of coal spontaneous combustion based on matter element analysis more scientific and reliable. The matter element analysis method is proved to be scientific and practical in the prediction of coal spontaneous combustion, which provides a new way of thinking and method for the prediction of coal spontaneous combustion. It is of great significance to lighten and prevent the spontaneous combustion of coal.
【学位授予单位】：太原理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TD752.2

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