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隧道建设(中英文) ›› 2017, Vol. 37 ›› Issue (S2): 115-120.DOI: 10.3973/j.issn.2096-4498.2017.S2.017

• 研究与探索 • 上一篇    下一篇

基于模糊神经网络的公路隧道照明控制系统研究

秦慧芳, 郭佑民, 罗荣辉   

  1. (兰州交通大学机电技术研究所, 甘肃 兰州 730070)
  • 收稿日期:2017-03-17 修回日期:2017-06-02 出版日期:2017-12-30 发布日期:2018-02-25
  • 作者简介:秦慧芳(1991—),女,山西忻州人,兰州交通大学机械电子工程专业在读硕士,研究方向为微机控制、智能控制。Email: 1109207342@qq.com。

Study of Illumination Control System of Highway Tunnel Based on Fuzzy Neural Network

QIN Huifang, GUO Youmin, LUO Ronghui   

  1. (Mechanical and Electronic Technology Institute,Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China)
  • Received:2017-03-17 Revised:2017-06-02 Online:2017-12-30 Published:2018-02-25

摘要:

针对目前隧道照明中存在的能源浪费问题,提出一种基于模糊神经网络算法的隧道照明控制策略,进一步降低隧道照明控制系统的能耗。具体是将实时采集的隧道口洞外亮度、过往的车流量及车速作为照明控制系统的输入量,隧道各照明段的回路调光值作为照明控制系统的输出量,搭建1个3输入-单输出的控制模型,重点对模型的建立和算法的机理及训练进行分析。最后通过仿真实验验证该算法在隧道照明中的节能效果,为现阶段隧道照明控制的相关研究提供一定的参考。

关键词: 公路隧道, 照明系统, 智能控制, 节能减排

Abstract:

The energy waste problem of illumination system in tunnel is serious. In order to reduce the energy consumption of tunnel illumination control system, a kind of tunnel illumination control strategy based on fuzzy neural network algorithm is put forward. The realtime collection of brightness outside the tunnel portal, the traffic flow and the vehicle speed are taken as input values of the illumination control system; the illumination loop dimming values collected from every illumination tunnel section are taken as the output values of the illumination control system; a illumination control model with tripleinput and singleoutput is established; and the mechanism and training of the establishment and caululation of the model are analyzed. The energysaving effect of the model for tunnel illumination control system is verified by experimental simulation, which can provide reference for present study of tunnel illumination control.

Key words: highway tunnel, illumination system, intelligent control, energy conservation and emission reduction

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