基于神经网络的隧道照明无级调光节能控制算法研究

Stepless Dimming Algorithm of Tunnel Lighting Energy-saving Control basedonN eural Network

高速公路隧道照明系统运营成本,随着照明时间的增加快速增加,如何在保证隧道交通安全的前提下,通过照明控制方法以节约高速公路隧道的能耗具有重要意义。本文针对阶梯式隧道照明设计的框架,提出了一种更加平滑的多层阶梯式无极调光模型及其算法。使用神经网络模型拟合洞外实际检测亮度、洞外交通量和交通流速度等指标与隧道内多层阶梯式各段照明需求亮度之间的函数关系,最终算出实时的隧道照明需求亮度与灯具期望功率之间的联系。仿真结果表明多层阶梯式无极调光控制算法的节能能耗达到50%。

With the rapid increase in mileage of highway tunnel, resulting in the high operation costs of a tunnel lighting system based on the maximum illumination design, energy saving become an important problem. A modified circuit subdivision and stepless dimming control algorithm based on neural network control method is given to reduce the tunnel lighting energy waste. According to predicted data of exterior environment luminance, traffic volume and speed, the energy- saving control modelof tunnel lighting is used to calculate the expected power of each sub-circuit lighting dimming lamps, and then the method present the relationship between tunnel lighting required luminance and expected power of lamps. The results show that energy saving up to 50% andluminance uniformity meet evaluation index of tunnel lighting based on circuit subdivision and stepless dimming control algorithm.