Research On Indoor Environmental Control System Based On Machine Vision

The most important function of comfort air conditioning in buildings is to serve the people who live and work in the room.In turn,for air conditioning,people are also one of the important links that affect the change of air conditioning load.Subject to the level of the previous generation of information technology,the conventional intelligent air conditioning system has some problems to be solved urgently,such as incomplete information parameter perception,lagging system sensing response,poor indoor air environment and low system energy saving efficiency.In order to reduce the influence of indoor volume inertia,heat transfer process and inherent delay of temperature regulator on the lag regulation of air conditioning operation,this paper explores a new method of introducing the change of population as a disturbance factor into the control strategy of air conditioning system,which is of great significance for improving indoor air quality and reducing system energy waste.The intelligent air conditioning control system proposed in this paper can sense the change of indoor population in time,which is more suitable for personnel-intensive public buildings.Therefore,a high-speed railway station in Beijing is selected as the research object,and the analysis and research are carried out by means of field measurement,data investigation and numerical simulation.Specifically,the research contents and theoretical results carried out in this paper are as follows :1.Based on the existing control strategy of VAV air conditioning system,an indoor environment control system based on machine vision is proposed.The influence of the change of the number of people on the cooling load of the air conditioner is analyzed from the perspective of the theoretical formula,and the relationship between the change of the number of people in the room and the adjustment of the air supply volume of the air conditioner is determined.After determining the control strategy of the system,a small system was built in the laboratory of a university.The accuracy of the system ’s population monitoring and the timeliness of the adjustment response were verified by experiments.2.Through the on-site measurement and investigation and analysis of the highspeed railway passenger station,it is found that :(1)The temperature fluctuation in the waiting hall is relatively large,and the minimum measured temperature is 25.2 °C,which is lower than the design specification requirements.(2)The measured cooling capacity of the chiller is 1965.05 k W,and the ACOP is 6.02,which meets the requirements of the specification.(3)The passenger flow at the station is small and the fluctuation is small.However,from the trend of data change,the passenger flow is deeply affected by the ticket gate of the departure station.In the 40 minutes around the ticket gate where the ticket is to be checked,the number of people will increase significantly.The data obtained can not only prove that the station air conditioning system still has a lot of room for improvement and energy saving potential,but also can be used to verify the accuracy of the model for subsequent numerical simulation.3.The influence of the optimized control strategy of conventional air conditioning on the indoor environment was studied by simulating the waiting room environment with Airpak.First of all,on the basis of the measured air conditioning operating parameters unchanged,the passenger flow is changed,and it is analyzed that when the passenger flow is small,but the air conditioning is running at high load,the indoor environment is cold,which affects the comfort of personnel and also causes energy waste.It is clarified that when the number of people in the room changes significantly,if the air conditioning fails to respond in time,during the transition period of the air conditioning response,the indoor environment quality will decrease,and even affect the comfort of personnel.Secondly,under the same passenger flow condition,the operating state of the indoor environment control system based on machine vision proposed in this paper is indirectly simulated by theoretically calculating the air supply state parameters for conditional input,and the environmental parameters under the operating conditions of the traditional air conditioning are compared and analyzed.It is further verified that the rapid response of the system proposed in this paper has a positive effect on maintaining a relatively stable and comfortable indoor environment.4.Using De ST energy consumption simulation software,the energy consumption changes of conventional control system and indoor environment control system based on machine vision are compared and studied.Specifically,the simulated operation of the two types of air-conditioning systems is distinguished by transforming the hourly passenger flow obtained from the survey into the hourly personnel work and rest mode in the software.The results show that compared with the conventional control system,the comprehensive energy consumption of the indoor environment control system based on machine vision is reduced by 16 %,which can effectively improve the energysaving benefits of the air-conditioning system.