公路隧道纵向通风神经网络在线控制
NeuralNetwork Online Control to Road Tunnel with LongitudinalVentilation
-
摘要: 基于神经网络方法建立了公路隧道纵向通风在线控制模型,结合交通模型、空气动力学模型及污染模 型,对隧道内污染物进行了通风控制过程的动态模拟.结果表明,当交通量在1 000~1 400辆/h、污染物基准排 放量在0. 008~0. 010 m3/(辆·km)范围内变化时,该系统能够依据交通量和污染物基准排放量的变化,相应增 加或减少风机开启台数,使隧道内的CO体积分数控制在限制值(150×10-6)以下.Abstract: An on-line controlmodel for road tunnelwith longitudinal ventilation was proposed based on neural networks and by combining traffic mode,l aerodynamics model and pollution mode.l Simulationwas conductedwith themode,l where the traffic volume changed from 1 000 to1 400 veh/h and the benchmark emission ratewas from 0. 008 to 0. 010m3/(veh·km). The results show that the proposed system increases or decreases the number of fans in realtime following the changes in the traffic volume and the benchmark emission rate, so that the volumetric fraction ofCO, as a control targe,t is controlled justunder the standard limit(150×10-6).
-
Key words:
- road tunnel /
- ventilation control /
- neuralnetwork /
- model /
- simulation
点击查看大图
计量
- 文章访问数: 1579
- HTML全文浏览量: 58
- PDF下载量: 292
- 被引次数: 0