山东科学
山東科學
산동과학
SHANDONG SCIENCE
2012年
4期
64-68
,共5页
隧道照明%RBF神经网络模型%隧道停车视距%智能控制
隧道照明%RBF神經網絡模型%隧道停車視距%智能控製
수도조명%RBF신경망락모형%수도정차시거%지능공제
tunnel illumination%RBF neural network model%tunnel stopping sight distance%intelligent control
为实现隧道内"灯光随车移动"控制技术,在隧道合适位置布设测速线圈,采用RBF神经网络模型预测相邻线圈间的车速。根据隧道特点建立隧道停车视距模型,从而确定了既符合实际又能保证行车安全的灯光长度。最后,给出照明灯智能控制思想。实例分析表明,当交通量低于3 000辆/天时,节能率能达到90%以上。
為實現隧道內"燈光隨車移動"控製技術,在隧道閤適位置佈設測速線圈,採用RBF神經網絡模型預測相鄰線圈間的車速。根據隧道特點建立隧道停車視距模型,從而確定瞭既符閤實際又能保證行車安全的燈光長度。最後,給齣照明燈智能控製思想。實例分析錶明,噹交通量低于3 000輛/天時,節能率能達到90%以上。
위실현수도내"등광수차이동"공제기술,재수도합괄위치포설측속선권,채용RBF신경망락모형예측상린선권간적차속。근거수도특점건립수도정차시거모형,종이학정료기부합실제우능보증행차안전적등광장도。최후,급출조명등지능공제사상。실례분석표명,당교통량저우3 000량/천시,절능솔능체도90%이상。
We deployed velocity coils at some suitable locations and employed RBF neural network to predict the velocity between two adjacent coils for the implementation of such intelligent control technology as light following vehicle.We also constructed a tunnel characteristic based tunnel stopping sight distance model,which determined a realistic and safe light length.We eventually presented the idea of smart illumination control.The analysis of practical cases shows that energy saving rate is more than 90% when the traffic throughput is lower than 3 000 pcu a day.