煤矿局部通风机智能控制系统研究及应用  

Research and Application of Intelligent Control System for Local Ventilation Fans in Coal Mines

作　　者：郜仲翔 尚宇雪 Gao Zhongxiang;Shang Yuxue(Jushan Coal Mine Co.,Ltd.,Shanxi Lanhua Group,Jincheng 048000,China)

机构地区：[1]山西兰花集团莒山煤矿有限公司,山西晋城048000

出　　处：《山东煤炭科技》2025年第4期174-178,共5页Shandong Coal Science and Technology

摘　　要：针对煤矿井下通风系统对通风需求的复杂性与动态性,提出一种基于Elman神经网络和模糊PID控制的局部通风机智能控制系统。系统通过Elman神经网络实时预测矿井通风需求,提高风量调节精度,结合模糊PID控制与变频调速技术,实现风机智能动态调节。莒山煤矿经过6个月应用测试,系统将风量误差控制在±0.81%以内,能在7 s内趋于稳定,系统年节约电能约192万kW·h,能耗降低25%,提升矿井通风安全性和经济效益。该研究为煤矿通风系统智能化控制提供了有效解决方案,具备广泛应用潜力。Aiming at the complexity and dynamics of ventilation requirements in coal mine downhole ventilation systems,a local ventilation fan intelligent control system based on Elman neural network and fuzzy PID control is proposed.The system uses Elman neural network to predict the mine ventilation requirements in real time,improve the accuracy of air volume regulation,and combine fuzzy PID control and frequency conversion speed regulation technology to achieve intelligent dynamic adjustment of the fan.After 6 months of application testing,the system of Jushan Coal Mine controls the air volume error within±0.81%,and can stabilize within 7 seconds.The system saves approximately 1.92 million kW·h of electricity annually,reduces energy consumption by 25%,and improves the ventilation safety and economic benefits of the mine.This study provides an effective solution for intelligentization control of coal mine ventilation systems and has broad application potential.

关 键 词：局部通风机 智能控制 神经网络 模糊控制 

分 类 号：TD724[矿业工程—矿井通风与安全]