基于遗传算法与Hardy-Cross方法的矿井通风机控制

Control of Mine Ventilation Fan Based on Genetic Algorithm and Hardy-Cross Method

针对矿井通风机系统控制的复杂问题,提出了一种遗传算法与Hardy-Cross方法相结合的矿井通风控制,强化了其在处理离散变量和非凸搜索空间中寻找全局最优解的能力。通过数学形式化定义问题并结合基尔霍夫定律,确立了通风机网络的优化模型。根据实际用风情况智能调节通风机的供风量,以实现能源节约和安全生产的目标。通过对某煤矿的通风案例深入研究和验证,风扇的配置在优化气流方面表现出了卓越性能。该研究不仅为矿山工程领域提供了新的优化思路和方法,也为通风机系统的管理提供了重要参考。

In response to the complex problem of controlling mine ventilation fan systems,a mine ventilation control method that combines genetic algorithm and the Hardy-Cross method has been proposed,which enhances its ability to find global optimal solutions in dealing with discrete variables and non-convex search spaces.By mathematically formalizing the problem and combining it with Kirchhoff′s law,an optimization model for the ventilation network has been established.According to the actual wind usage situation,the supply volume of the ventilation fan is intelligently adjusted to achieve the goals of energy saving and safe production.Through in-depth research and verification of the ventilation case of a coal mine,the fan configuration has shown excellent performance in optimizing airflow.This research not only provides new optimization ideas and methods for the field of mining engineering,but also provides important references for the management of ventilation system.