煤矿工作面需风量预测及通风机智能控制  

Prediction and Intelligent Control of Coal Mine Ventilator Air Requirement

作　　者：王海鹏 Wang Haipeng(Yang Coal Group Shouyang Jingfu Coal Co.,Ltd.,Jinzhong Shanxi 045000,China)

机构地区：[1]阳煤集团寿阳景福煤业有限公司,山西晋中045000

出　　处：《机械管理开发》2023年第8期212-213,218,共3页Mechanical Management and Development

摘　　要：为达到对通风机风速控制的准确性和解决传统风速控制方式的问题,在对通风机简单概述的基础上,对工作面需风量的预测展开研究,确定需风量预测的模型;对比了传统PID控制策略、模糊算法控制策略以及T-S模糊神经控制策略的响应特性和超调量,确定采用T-S模糊神经控制策略实现通风机的智能控制,并完成了相关硬件的选型。In order to achieve the accuracy of ventilator air speed control and solve the problems of traditional air speed control methods,based on a brief overview of the ventilator,the prediction of air demand at the working face is studied to determine the model of air demand prediction;the response characteristics and overshooting amount of traditional PID control strategy,fuzzy algorithmic control strategy and T-S fuzzy neural control strategy are compared to determine the inteligent control of the ventilator by using T-S fuzzy neural control strategy and the selection of related hardware is completed.control strategy to realize the intelligent control of the ventilator,and complete the selection of related hardware.

关 键 词：通风机 需风量 节能控制 T-S模糊神经控制策略 响应时间 

分 类 号：TD724[矿业工程—矿井通风与安全]