矿井灾变条件含尘大气环境泛谱热辐射特性机理研究

发布时间：2018-08-02 07:33

【摘要】：煤炭作为我国目前最主要的化石能源,占比达到了一次性能源消费的70%以上,且超过90%的煤炭生产主要来自于地下井工煤矿。随着矿井机械化水平的提高以及开采深度的增加,矿井灾害产生的有毒有害气体以及采掘等作业产生的矿尘粒子大量弥散于巷道内并随通风污染整个矿井网络的大气环境,严重威胁煤矿安全生产及职业健康。本文从光学监测识别灾害时期矿井大气污染物的角度出发,开展了含尘大气环境红外光谱辐射特性建模与实验、数值分析,为矿井灾害的光学预警方法提供了理论基础和数据支持。首先,对井下工作面作业产生的固体污染物进行了FT-IR测试并根据色散理论获得了矿尘粒子的光谱复折射性质,通过Mie模型求解了矿尘颗粒的红外光散射特性,分析了作业工况对弥散矿尘粒子系光谱衰减特性的影响。针对矿井灾变气体(CH4、CO、SO2、NO2等),采用HITRAN谱线数据及窄谱带模型建立了矿井大气典型灾害气体的红外光谱吸收特性数据库,研究了巷道环境压力、温度等因素对吸收强度和吸收峰的影响。其次,基于矿井大气污染物基本光学性质并结合其空间分布,建立了非灰、吸收、发射、散射参与性介质内光辐射传输模型,采用离散坐标法数值求解得到了矿井含尘大气环境的红外辐射特性。研究了含尘、含湿、含惰矿井大气光学背景的谱带吸收及消光特性,分别针对矿井瓦斯、自燃、污染物排放及爆破作业等过程仿真分析了灾变条件下含尘大气的光谱热辐射特性。最后,以瓦斯涌出条件下含尘大气环境光学监测为案例,进行了矿井灾害红外信息辨识方法研究。根据瓦斯扩散矿井含尘大气环境的红外光谱选择性,选取四个独立谱带结合随机微粒群算法建立了辐射反问题模型。结果表明,同时反演获得的瓦斯和矿尘浓度与其真值保持一致,其相对误差在10%以内。考虑到井下复杂作业环境及实时监测要求,开展了多通道红外探测光学窗口的优化设计,讨论了含尘光学背景及信号噪声等因素对反演精度的影响。
[Abstract]:As the most important fossil energy in China, coal accounts for more than 70% of the one-time energy consumption, and more than 90% of the coal production comes from underground coal mines. With the improvement of mine mechanization level and the increase of mining depth, the toxic and harmful gases produced by mine disasters and the dust particles produced by mining and other operations are dispersed in large quantities in the roadway and pollute the atmospheric environment of the whole mine network with ventilation. It is a serious threat to coal mine production safety and occupational health. In this paper, from the view of optical monitoring and identification of mine air pollutants during disasters, the infrared spectral radiation characteristics of dust-bearing atmosphere are modeled and experimented, and numerical analysis is carried out. It provides theoretical basis and data support for optical warning method of mine disaster. Firstly, the solid pollutants produced in underground working face are tested by FT-IR and the spectral complex refraction properties of mine dust particles are obtained according to dispersion theory. The infrared light scattering characteristics of mine dust particles are solved by Mie model. The influence of operating conditions on the spectral attenuation characteristics of the dispersion dust system is analyzed. Aiming at mine disaster gas (Ch _ 4, CO _ (2) so _ (2) O _ (2), the infrared spectral absorption characteristic database of mine atmospheric typical disaster gas was established by using HITRAN spectral line data and narrow spectral band model, and the tunnel environmental pressure was studied. The influence of temperature and other factors on the absorption intensity and absorption peak. Secondly, based on the basic optical properties of mine air pollutants and their spatial distribution, a non-gray, absorption, emission and scattering model of light radiation transfer in participatory media is established. The infrared radiation characteristics of mine dust-bearing atmosphere are obtained by using discrete coordinate method. The absorption and extinction characteristics of dust, wet and inerted mine atmospheric optical background are studied. The characteristics of spectral thermal radiation of dust-containing atmosphere under catastrophic conditions are analyzed by simulation of pollutant discharge and blasting operation. Finally, the infrared information identification method of mine disaster is studied by taking the optical monitoring of dust-bearing atmosphere under the condition of gas emission as an example. According to the infrared spectral selectivity of gas diffusion mine dust-bearing atmosphere, four independent spectral bands were selected and stochastic particle swarm optimization (RPSO) algorithm was used to establish the radiation inverse problem model. The results show that the concentration of gas and ore dust obtained by simultaneous inversion is consistent with its true value, and the relative error is less than 10%. Considering the complex working environment and real-time monitoring requirements, the optimization design of multi-channel infrared detection optical window is carried out, and the influence of dust optical background and signal noise on inversion accuracy is discussed.
【学位授予单位】：中国矿业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TD714

【参考文献】