基于BP神经网络和模糊控制的智能通风系统设计  

Design of Intelligent Ventilation System Based on BP Neural Network and Fuzzy Control

作　　者：闫向彤[1] 杨琦 Yan Xiangtong;Yang Qi(School of Mechnical Engineering,Xi’an Science and Technology,Xi’an 710054,China)

机构地区：[1]西安科技大学机械工程学院,西安710054

出　　处：《煤矿机械》2021年第2期174-176,共3页Coal Mine Machinery

摘　　要：针对传统的井下局部通风机恒速运行及浪费电能的缺陷,提出了一种基于BP神经网络和模糊控制的智能通风系统。将井下瓦斯浓度、温度、湿度及煤尘等参数输入到BP神经网络模型中,对井下风量进行预测,通过当前风量与预测风量的对比,运用模糊控制算法对变频器电压进行调节,从而实现对变频器输出频率的控制,有效降低了局部通风机的耗电量,对煤矿安全生产具有重要的现实意义。Aiming at the defects of traditional mine local ventilator of constant speed operation and waste electrical energy,proposed an intelligent ventilation system based on BP neural network and fuzzy control.The mine gas concentration,temperature,humidity and coal dust parameters were input to the BP neural network model to forecast the underground air volume.Through the comparison of current air volume and forecast air volume,the fuzzy control algorithm was used to the inverter voltage adjustment,so as to realize to control the inverter output frequency,effectively reduced the local ventilator power consumption,which has important practical significance for coal mine safety production.

关 键 词：BP神经网络 模糊控制 局部通风机 需风量预测 智能通风 

分 类 号：TD724.4[矿业工程—矿井通风与安全]