基于神经网络的矿井通风可靠性预计研究

Reliability Prediction of Mine Ventilation Based on Neural Network

矿井通风系统是煤矿生产中的重要组成部分,通风系统的稳定、可靠运行关系着煤矿安全生产和井下人员的生命安全。在对矿井通风系统可靠性影响因素分析的基础上,分析了通风网络单元模型,并确定了基于神经网络算法的通风系统可靠性预计方案;根据通风系统可靠性预计因素确定了可靠性预计神经网络的算法构型及各层神经元参数,通过对神经网络预计模型的仿真,得到该预计模型仿真结果与实际结果的对比情况,并确定该预计模型的可行性。

Mine ventilation system is an important part of coal mine production.The stable and reliable operation of the ventilation system is related to the safety of coal mine production and the life safety of underground personnel.Based on the analysis of influencing factors of mine ventilation system reliability,the ventilation network unit model is analyzed,and the reliability prediction scheme of ventilation system based on neural network algorithm is determined.According to the reliability prediction factors of ventilation system,the algorithm configuration of reliability prediction neural network and the parameters of each layer of neural network are determined.Through the simulation of the neural network prediction model,the comparison between the simulation results of the prediction model and the actual results is obtained,and the feasibility of the prediction model is determined.