基于改进鸽群算法的矿井风量智能调节方法

Mine intelligent air volume regulation method based on improved pigeon-inspired algorithm

为解决矿井风量调节效率低的问题,建立矿井智能风量调节模型。为达到一体化求解,将其转换为最小欧式距离的求解问题;基于灵敏度分析了分支的可调特性,对传统鸽群算法进行改进,引入一种基于切比雪夫滤波器对罗盘算子进行非线性变化的改进,并在地图搜索阶段引入莱芜飞行,从而避免陷入局部最优。引入一种实数编码的量子表示方法改进算法的收敛方向,并对鸽群淘汰机制进行改进。应用三维通风仿真系统对调节结果进行验证,在对5种不同类型巷道的150次增、减风调节中,严重偏差只出现2次,准确率达到98.6%,证明该方法能够高效、稳定地对矿井风量进行调节。

To solve the problem of low efficiency in air volume regulation in mines,a mine intelligent air volume regulation model was established.In order to achieve the purpose of integrated solution,it was transformed into the solution problem of minimum Euclidian distance.The adjustable characteristics of branches were analyzed based on sensitivity.The traditional pigeon-inspired algorithm was improved,a Chebyshev filter was introduced to improve the nonlinear variation of the compass operator,the Levy Flight is introduced in the map search stage to avoid falling into local optimum,a quantum representation method of real number coding was introduced to improve the convergence direction of the algorithm,and the pigeon group elimination mechanism was improved.The three-dimensional ventilation simulation system was applied to verify the regulation results.In the 150 air increase and decrease regulation of 5 different types of tunnel lateral,only 2 of them were serious deviation,the accuracy rate reached 98.6%,which proved that this method can effectively and stably regulate the mine air volume.