摘要
为保证施工通风质量、控制施工通风成本、降低碳排放、解决智能控制模型对隧道施工通风系统的适用性问题,首先,采用文献调研和理论分析结合的方法建立基于CO体积分数的爆破工况和出渣工况下隧道施工通风需风量理论模型;其次,设计应用于隧道施工通风系统的PID控制模型、模糊PID(Fuzzy PID)控制模型和RBF神经网络PID控制模型;最后,采用数值仿真的方法,基于MATLAB对各控制模型应用于隧道施工通风系统理论模型的参数确定和控制效果进行对比研究。结果表明:在隧道施工通风系统中,控制模型性能和抗干扰性有一定的负相关性,PID控制模型由于参数调节的便捷性使其在理论响应性能上较为优异,但Fuzzy PID控制模型或RBF-PID控制模型可更好地响应实际工程对于抗干扰和性能的需求。
To ensure construction ventilation quality,control construction ventilation costs,reduce carbon emissions,and improve the applicability of intelligent control model to tunnel construction ventilation systems,a theoretical model based on the CO volume fraction under blasting and mucking conditions is established based on literature research and theoretical analysis methods.In addition,proportional-integral-derivative(PID),fuzzy PID,and radial basis function(RBF)neural network-PID control models are designed for the ventilation systems.Finally,a numerical simulation is performed in MATLAB to compare the parameter determination and control effect of the different control models applied to the proposed theoretical model.The results show that the performance of the control models is negatively correlated with anti-interference to a certain extent.Among the investigated models,PID control model exhibits the best theoretical response because of its convenient parameter determination,whereas fuzzy PID and RBF-PID control models best meet the anti-interference and performance requirements of actual projects.
作者
张佳鹏
郭春
ZHANG Jiapeng;GUO Chun(College of Civil Engineering,Southwest Jiaotong University,Chengdu 610031,Sichuan,China;Key Laboratory of Transportation Tunnel Engineering,Ministry of Education,Southwest Jiaotong University,Chengdu 610031,Sichuan,China)
出处
《隧道建设（中英文）》
CSCD
北大核心
2023年第7期1153-1160,共8页
Tunnel Construction
基金
“十三五”国家重点研发计划(2019YFC0605104)
四川省社会科学规划项目(SC22B031)
四川省教育科研资助金项目(SCJG20A120)
四川省交通运输科技项目(2021-ZL-04)。
关键词
隧道施工通风
PID控制
模糊控制
RBF神经网络
能耗
tunnel construction ventilation
proportional-integral-derivative control
fuzzy control
radial basis function neural network
energy consumption
