Research On Energy Saving Of Subway Station Lighting Based On Population Density Estimation

As a typical underground building,artificial lighting is the main source of light for subway stations.In recent years,the rapid development of subway construction has led to an increase in energy consumption in subway station lighting systems.At the same time,the development of deep learning and intelligent control technology has provided new technical means for lighting energy conservation.Therefore,the study of lighting energy saving in subway stations has important practical significance.Based on the characteristics of subway station passenger flow and artificial light environment,this paper proposes a subway station lighting energy-saving control method based on population density estimation.This method realizes the illumination by dynamically estimating the crowd density of the subway station and dynamically adjusting the output power of the LED lamp.Energy saving purposes.The main tasks completed are as follows:(1)Research on population density estimation algorithm.Based on the deep learning theory,the population density estimation model was established by convolutional neural network.The training set and the real density map were generated by MATLAB.The model data was trained and tested by using the public dataset and the real shot image of the subway station.The test results show that the model can realize the real-time estimation of the population density of the subway station,and the estimation accuracy meets the application requirements,and the time is low.(2)Research on lighting control strategy.According to the characteristics of different functional areas of the subway station and the passengers' demand for artificial lighting,corresponding lighting control strategies are proposed for the platform and the station.The strategy comprehensively considers the influence of crowd density and advertising lighting on the lighting of the public area of the subway station.Based on the division of the network format and the control of the lighting of the lamps,the pulse dimming(PWM)technology is adopted to realize the LED dimming control.(3)Design and implementation of LED dimming controller.Using the crowd density estimation results,an LED dimming controller based on Open MV machine vision module was designed.It has been verified by experiments that the brightness of LED can change in real time with the density of the crowd,and the brightness changes gently and without flicker.In addition,with the lighting design software DIALux evo,the average illuminance of the subway station platform and station hall at different population densities is calculated.Finally,by comparing the calculated illuminance and the measured illuminance in different situations of the operation time of the subway station,energy efficiency analysis is carried out from two angles of illumination and power consumption.The results show that the power saving rate of subway station and station floor can reach62.7% and 46.8%,respectively,which fully confirms the effectiveness of subway station lighting control method based on population density estimation.