基于相继平均移动法通风网络全局风量优化

Global optimization adjustment of ventilation network based on successive average moving method

针对井下风流状态、巷道面积动态变化,矿井各巷道风量测试值与实际风量间存在误差,直接影响后续通风信息管理及应急预案制定问题,对测试风量进行优化修正,最小化其与实际风量差值。使用最小二乘理念,以节点风量平衡、风量优化幅度决策做约束条件,各节点两次修正值差式满足设定精度做结束逻辑,针对矿井通风网络构建全节点进出风量差值平方和最小化目标函数,并使用相继平均移动算法解算,实现对通风网络全局分支测试风量整体优化,使各分支风量更贴近实际风量。为验证算法合理性,对李雅庄煤矿测试风量进行仿真模拟。研究结果表明:针对通风网络全局,在优化幅度内经98次迭代,所有节点风量进出平差值总和仅为1.0×10^(-5)m^(3)/s,验证了所提出模型算法的准确性。

Due to the dynamic changes of the underground air flow status and the roadway area,there is an error between the air volume of each roadway in the mine and the actual air volume measured by the ventilation resistance,which directly affects the subsequent ventilation information management and emergency plan formulation.The test air volume needs to be optimized and corrected to minimize the difference between it and the actual air volume.Using the concept of least squares,the node air volume balance and air volume optimization range decision are used as constraints.The two correction value differences of each node meet the set accuracy as the ending logic,and the square sum of the node air volume difference of each node in the mine ventilation network is constructed.Minimize the objective function,use the successive average moving algorithm to solve the overall optimization of the global branch test air volume of the ventilation network so that the air volume of each branch is closer to the actual air volume.In order to verify the rationality of the algorithm,the test air volume simulation of LiYazhuang coal mine was carried out.The research results show that for the overall ventilation network,after 98 iterations within the optimization range,the total value of the air volume in and out of all nodes is 1.0×10^(-5)m^(3)/s,which verifies the accuracy of the proposed model algorithm.