基于模糊神经网络的高速公路隧道照明节能控制系统研究

Research on energy-saving control system for highway tunnel lighting based on fuzzy neural network

针对高速公路隧道照明控制系统存在的亮度控制不合理、能耗高等问题,提出一种基于模糊神经网络的高速公路隧道照明节能控制系统,并分别从硬件和软件两方面进行详细设计。系统硬件设计中,设计了系统硬件架构示意图,主要包括电容、PLC等在内的主控制器、从控制器和终端控制器,通过电流和电压信号变化控制提供硬件条件;软件设计中,通过图像采集技术,将获取到的图像进行二值化分离,利用车灯实现高速公路隧道车流量检测,建立模糊神经网络,设置网络的输入层变量和输出层变量,确定模糊子集以及模糊子集隶属函数,通过控制照明灯具的开关时间来调节亮度,实现高速公路隧道照明节能控制系统的设计。系统测试结果表明:在不同车速变量下,设计的照明节能控制系统在能够提供有效的照明功能下,减少了照明能耗。

In response to the problems of unreasonable brightness control and high energy consumption in the highway tunnel lighting control system,a energy-saving control system for highway tunnel lighting based on fuzzy neural network is proposed,and detailed design is carried out from both hardware and software aspects.In the system hardware design,a schematic diagram of the system hardware architecture was designed,mainly including the main controller,slave controller,and terminal controller,including capacitors,PLCs,etc.,providing hardware conditions through current and voltage signal changes control;In software design,image acquisition technology is used to binary separate the obtained images,and vehicle flow detection in highway tunnels is achieved using car lights.A fuzzy neural network is established,and the input and output layer variables of the network are set to determine the fuzzy subset and fuzzy subset membership function.The brightness is adjusted by controlling the switching time of lighting fixtures,achieving the design of an energy-saving control system for highway tunnel lighting.The system test results indicate that under different vehicle speed variables,the designed lighting energy-saving control system can reduce lighting energy consumption while providing effective lighting functions.