摘要
为了揭示煤矿巷道瓦斯气体浓度分布规律,提出一种基于高斯烟羽模型的煤矿巷道瓦斯气体浓度分布重建方法。该方法根据煤矿巷道环境特点,采用虚拟像源法,引入巷道空间结构对气体的反射作用,建立煤矿巷道有限空间高斯烟羽模型,参照Pasquill-Gifford气体扩散系数表达式构建煤矿巷道瓦斯气体扩散系数函数;采用Sobol′方法对模型参数进行敏感性分析,得到各参数的总效应指数,并引入气体涌出速度调整参数β;采用粒子群算法对扩散系数及β进行寻优,得到扩散系数和β的最优拟合,以进一步优化瓦斯气体在当前空间的扩散模型,提高模型预测精度,达到重建此空间瓦斯气体浓度分布的目的。实验结果表明,该方法能较好地重建煤矿巷道瓦斯气体浓度分布,对实现煤矿智能检测提供更好的理论支撑。
A Gaussian plume model based reconstruction method of gas concentration distribution in coal mine roadway is proposed to reveal the law of gas concentration distribution.According to the environmental characteristics of the coal mine road-way,the virtual image source method is adopted to establish the limited space Gaussian plume model of coal mine roadway by utilizing the reflection effect of roadway space structure on gas.The gas diffusion coefficient function of coal mine roadway is con-structed by referring to Pasquill-Gifford(PG)gas diffusion coefficient expression.Sobol′method is used to analyze the sensitivi-ty of model parameters to obtain the total effect index of each parameter.In addition,gas emission rate is introduced to adjust parameterβ.Particle Swarm Optimization(PSO)is used to optimize the diffusion coefficient andβto obtain their optimum fit-ting,so as to further optimize the diffusion model of gas in the current space,improve the prediction accuracy of the model,and achieve the purpose of reconstructing the gas concentration distribution in the current space.The experimental results show that the proposed method can better reconstruct the gas concentration distribution in the coal mine roadway,and provide better theoretical support for the realization of intelligent detection in the coal mine.
作者
聂珍
马宏伟
刘鹏
NIE Zhen;MA Hongwei;LIU Peng(College of Mechanical Engineering,Xi’an University of Science and Technology,Xi’an 710054,China;Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Monitoring,Xi’an 710054,China)
出处
《现代电子技术》
2021年第7期127-132,共6页
Modern Electronics Technique
基金
陕西省重点研发计划项目(2018ZDCXL-GY-06-04)
国家自然基金重点项目(51834006)
国家自然基金面上项目(51975468)。
