ISSN 2096-4498 CN 44-1745/U
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
秦慧芳, 郭佑民, 罗荣辉
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作者简介:
QIN Huifang, GUO Youmin, LUO Ronghui
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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 realtime 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 tripleinput and singleoutput is established; and the mechanism and training of the establishment and caululation of the model are analyzed. The energysaving 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
中图分类号:
U 45
秦慧芳, 郭佑民, 罗荣辉. 基于模糊神经网络的公路隧道照明控制系统研究[J]. 隧道建设, 2017, 37(S2): 115-120.
QIN Huifang, GUO Youmin, LUO Ronghui. Study of Illumination Control System of Highway Tunnel Based on Fuzzy Neural Network[J]. Tunnel Construction, 2017, 37(S2): 115-120.
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