矿井通风阻力系数反演研究
发布时间：2018-07-23 08:37
【摘要】：矿井通风网络解算的理论和算法研究早在70年代就已经成熟,但时至今日通风网络解算仍然没有在矿井生产实际应用中得到广泛的应用.通风网络解算应用的3大瓶颈问题之一的通风阻力系数“测不准,总在变”的问题,时至今日该问题尚未解决,阻碍了通风网络解算在实际中的应用.巷道风阻可通过经验公式计算和通风阻力测试获取.风阻经验公式通常只是一些特殊情况的近似归纳,一些常量参数取值更多的依赖人为经验,存在较大的主观性误差；而现场测试工作量非常大且费时、费力.无论是经验公式还是现场测试,得到的风阻数据都存在误差,使得仿真计算的结果与实际的通风系统不匹配.如何通过少量代表性巷道风量、节点压力等有限的实测数据,反演矿井通风系统阻力系数,这是一项值得研究的课题.目前国内外关于通风阻力系数反演研究较少,基于国家自然基金资助项目(60772159)《基于仿真技术的矿井通风系统智能诊断系统研究》,开展本文研究工作.从流体网络三大基本定律出发,建立通风阻力系数反演的矩阵方程组形式.无论是多测点一次观测还是少测点多次观测条件下,利用有限的巷道风量和节点压力观测数据来反演通风系统中的各条巷道风阻,由于方程数小于未知变量个数,反演问题始终存在多解的情况,通风阻力系数反演问题是不适定的.基于最小二乘原理建立了通风阻力系数反演的数学模型,以实测压力与与计算压力的偏差以及实测风量与计算风量的偏差为目标函数,综合考虑了压力、风量以及通风阻力系数范围约束,通过该模型的建立将通风阻力系数反演问题转化非线性优化问题.采用遗传算法和粒子群算法来求解基于最小二乘原理的通风阻力系数反演的优化问题.针对通风阻力系数反演问题,对遗传算法和粒子群算进行了改进,增强算法的全局搜索和局部搜索能力.上述研究基础上,可以依据观测点相对灵敏度选择合适的观测数据进行通风阻力系数反演.结合通风系统灵敏度理论和聚类分析理论,提出了一种基于反映通风系统阻力系数变化的巷道风量测点和节点压力测点布置方法,对通风系统中可以观测的巷道、节点进行分类,寻找少量代表性强的分支风量测点和节点压力测量,最大可能的反映通风系统的实际运行状态,减少测试工作量.最后通过实例描述了基于粒子群算法的寺河矿二号井通风阻力系数反演过程,验证了反演方法的可行性,为进一步的研究通风阻力系数反演问题以及实际工程应用奠定了基础,具有重要的指导意义.
[Abstract]:The theory and algorithm of mine ventilation network calculation have been mature since 1970s, but the ventilation network calculation has not been widely used in mine production. One of the three bottleneck problems in the application of ventilation network calculation is the problem of "uncertainty, total change" of ventilation resistance coefficient. Up to now, this problem has not been solved, which hinders the application of ventilation network calculation in practice. Roadway wind resistance can be calculated by empirical formula and ventilation resistance test. The empirical formula of wind resistance is usually an approximate induction of some special cases, and some constant parameters are more dependent on human experience, and there is a large subjective error, while the field test work is very heavy, time-consuming and laborious. No matter the empirical formula or the field test, there are errors in the wind resistance data, which makes the simulation results do not match the actual ventilation system. How to retrieve the resistance coefficient of mine ventilation system through a small amount of representative tunnel air volume, node pressure and other limited measured data is a subject worth studying. At present, there are few researches on the inversion of ventilation resistance coefficient at home and abroad. Based on the project funded by the National Natural Fund (60772159) < Research on Intelligent diagnosis system of Mine ventilation system based on Simulation Technology ", the research work is carried out in this paper. Based on the three basic laws of fluid network, the matrix equations of ventilation resistance coefficient inversion are established. Under the condition of multiple observation points or multiple observation points, the wind resistance of each tunnel in ventilation system can be retrieved by using the limited observation data of tunnel air volume and node pressure, because the number of equations is less than the number of unknown variables. The inversion problem always has multiple solutions, and the ventilation resistance coefficient inversion problem is ill-posed. Based on the least square principle, a mathematical model of ventilation resistance coefficient inversion is established. The deviation between measured and calculated pressure and between measured and calculated air volume is taken as the objective function, and the pressure is considered synthetically. Through the establishment of the model, the inversion problem of ventilation resistance coefficient is transformed into a nonlinear optimization problem. Genetic algorithm and particle swarm optimization algorithm are used to solve the optimization problem of ventilation resistance coefficient inversion based on least square principle. For the problem of ventilation resistance coefficient inversion, genetic algorithm and particle swarm optimization are improved to enhance the global and local search ability of the algorithm. Based on the above research, the ventilation resistance coefficient can be retrieved according to the relative sensitivity of observation points. Based on the sensitivity theory of ventilation system and the cluster analysis theory, a method of layout of air flow measurement points and nodal pressure measuring points of roadway based on the change of resistance coefficient of ventilation system is proposed. The nodes are classified to find a small number of representative branch air flow measurement points and node pressure measurement to reflect the actual operating state of the ventilation system and reduce the test workload. Finally, the inversion process of ventilation resistance coefficient of Sihe No. 2 well based on particle swarm optimization is described, which verifies the feasibility of the inversion method, and lays a foundation for further research on the inversion of ventilation resistance coefficient and its practical engineering application. It has important guiding significance.
【学位授予单位】：辽宁工程技术大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TD724
本文编号：2138830
[Abstract]:The theory and algorithm of mine ventilation network calculation have been mature since 1970s, but the ventilation network calculation has not been widely used in mine production. One of the three bottleneck problems in the application of ventilation network calculation is the problem of "uncertainty, total change" of ventilation resistance coefficient. Up to now, this problem has not been solved, which hinders the application of ventilation network calculation in practice. Roadway wind resistance can be calculated by empirical formula and ventilation resistance test. The empirical formula of wind resistance is usually an approximate induction of some special cases, and some constant parameters are more dependent on human experience, and there is a large subjective error, while the field test work is very heavy, time-consuming and laborious. No matter the empirical formula or the field test, there are errors in the wind resistance data, which makes the simulation results do not match the actual ventilation system. How to retrieve the resistance coefficient of mine ventilation system through a small amount of representative tunnel air volume, node pressure and other limited measured data is a subject worth studying. At present, there are few researches on the inversion of ventilation resistance coefficient at home and abroad. Based on the project funded by the National Natural Fund (60772159) < Research on Intelligent diagnosis system of Mine ventilation system based on Simulation Technology ", the research work is carried out in this paper. Based on the three basic laws of fluid network, the matrix equations of ventilation resistance coefficient inversion are established. Under the condition of multiple observation points or multiple observation points, the wind resistance of each tunnel in ventilation system can be retrieved by using the limited observation data of tunnel air volume and node pressure, because the number of equations is less than the number of unknown variables. The inversion problem always has multiple solutions, and the ventilation resistance coefficient inversion problem is ill-posed. Based on the least square principle, a mathematical model of ventilation resistance coefficient inversion is established. The deviation between measured and calculated pressure and between measured and calculated air volume is taken as the objective function, and the pressure is considered synthetically. Through the establishment of the model, the inversion problem of ventilation resistance coefficient is transformed into a nonlinear optimization problem. Genetic algorithm and particle swarm optimization algorithm are used to solve the optimization problem of ventilation resistance coefficient inversion based on least square principle. For the problem of ventilation resistance coefficient inversion, genetic algorithm and particle swarm optimization are improved to enhance the global and local search ability of the algorithm. Based on the above research, the ventilation resistance coefficient can be retrieved according to the relative sensitivity of observation points. Based on the sensitivity theory of ventilation system and the cluster analysis theory, a method of layout of air flow measurement points and nodal pressure measuring points of roadway based on the change of resistance coefficient of ventilation system is proposed. The nodes are classified to find a small number of representative branch air flow measurement points and node pressure measurement to reflect the actual operating state of the ventilation system and reduce the test workload. Finally, the inversion process of ventilation resistance coefficient of Sihe No. 2 well based on particle swarm optimization is described, which verifies the feasibility of the inversion method, and lays a foundation for further research on the inversion of ventilation resistance coefficient and its practical engineering application. It has important guiding significance.
【学位授予单位】：辽宁工程技术大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TD724
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