Investigation On Intelligent Control Method Of Indoor Temperature Of Air Conditioning In Public Buildings Based On Wearable Sensing Of Human Thermal Sensation

Optimal operation control of air conditioning system in public buildings is an important technical measure to ensure thermal comfort of building environment.reduce energy consumption and achieve energy saving and emission reduction of buildings.It has been a difficult and hot issue in domestic and foreign research.and is gradually widely used in practical engineering.At the same time,the thermal comfort of air conditioning environment and the human thermal sensation are also the focus of many international institutions in the field of architecture for a long time.the results of which provide a scientific basis for the formulation and improvement of many standards and norms.However,there is an obvious disconnect between the research and application of the optimized operation control of air conditioning system and the thermal comfort of building environment,especially the real-time human thermal sensation.It is relatively common that in the actual control engineering of air conditioning system,human(group)thermal sensation is not introduced into the process control of air conditioning system in real time.This problem is manifested in engineering as the wallmounted temperature controller is generally used in air conditioning room to realize the setting,monitoring and controlling of the indoor temperature of the whole room.However,due to the installation position of the wall thermostat(usually installed on the inner wall near the door)is far away from the internal air conditioning area,the wall thermostat cannot reflect the real time temperature and humidity changes in the air conditioning area,let alone the real time human(group)thermal sensation in the air conditioning area.In addition,the actual survey shows that the setting value of air conditioning room temperature in public buildings in summer and winter is generally too low in summer and too high in winter,and the setting value of room temperature cannot be automatically reset with the change of human thermal sensation.The disconnection between the optimal operation control of the above two types of air conditioning systems and the real-time human(group)thermal sensation is not only conducive to further improving the indoor thermal comfort of the air conditioning system,but also increases the energy consumption of the air conditioning system,which needs to be solved urgently.In recent years.the development and successful application of artificial intelligence technologies such as internet of things,wearable computer and machine learning in related fields provide new technical approaches to solve key problems such as real-time monitoring of human(group)thermal sensation,automatic setting of room temperature setting value and intelligent control of room temperature in air-conditioned rooms.Therefore,this dissertation aims to solve the disconnection problem between the optimization operation control of air conditioning system in public buildings and the human(group)thermal sensation in engineering application,further improve the thermal comfort of air conditioning environment and reduce the energy consumption of system operation,and adopts the method of combining theoretical research,technical development and experimental research to solve the key problems of online monitoring and evaluation of human(group)thermal sensation and intelligent control of air temperature in the air conditioning environment of large public buildings,in order to obtain a new intelligent control method of air temperature of public buildings based on the wearable sensing of human(group)thermal sensation.First of all,the development of internet of things monitoring technology for human thermal sensation in the air conditioning environment of public buildings is the premise and foundation to solve the problem of intelligent room temperature control of air conditioning based on wearable sensing of human(group)thermal sensation.This dissertation introduces intelligent wristband technology in this subject area,put forward the intelligent wristband-smartphonesserver-air conditioning controller-the end of the air conditioning human thermal sensation physiology parameters real-time monitoring and data transmission technology,developed a smart phone APP for room temperature intelligent control and data management software system,realize the intelligent wristband and air conditioning controller direct communication.The test results show that the intelligent wristband real-time monitoring system for human thermal sensation physiological parameters can operate safely and stably.Secondly,the establishment of the correlation prediction model between human thermal sensation and human physiological parameters is the primary theoretical basis to solve the problem of intelligent regulation of air conditioning room temperature based on wearable sensing of human(group)thermal sensation.In this dissertation,the correlation between human thermal sensation and physiological parameters such as wrist skin temperature and heart rate is studied,and the linear prediction model and T-S fuzzy prediction model of human thermal sensation are established.The analysis results show that these models have high prediction accuracy.Moreover,in order to meet the application requirements of online control,this dissertation further proposes an online correction method for the linear prediction model of human thermal sensation,and verifies the effectiveness and applicability of the correction method.Thirdly,the online prediction and evaluation of the group thermal sensation of air conditioning environment in public places is another key theoretical problem to solve the realtime monitoring and evaluation of the human thermal sensation of public buildings and the intelligent regulation of room temperature.In this dissertation.a fuzzy comprehensive evaluation method of group thermal sensation is proposed.The experiments prove that this method can effectively evaluate group thermal sensation.To use the method into control process of the air conditioning system,the dissertation proposes linear adjustment algorithm of the air conditioning room temperature setting based on wearable sensing of group thermal sensation,experimental study on the summer air conditioning system in the thermal sensation based on wearable sensing of group thermal sensation and the traditional operational properties of room temperature set point control method,the results show that the former has better thermal comfort than the latter,and the daily power consumption of the air conditioning system is reduced by 13.8%.Fourthly,the intelligent control method of air conditioning room temperature based on wearable sensing of group thermal sensation is the theoretical basis to realize energy saving and optimal operation of air conditioning system,and the key to further solve the disconnection between intelligent control of air conditioning system and human thermal sensation.This dissertation proposes room temperature fuzzy control method based on wearable sensing of group thermal sensation,the experimental studies on the summer air conditioning system have been conducted in using based on room temperature fuzzy control method based on wearable sensing of group thermal sensation,thermal sensation feedback-based control and temperature set point-based control.The results show that the room temperature fuzzy control method based on wearable sensing of group thermal sensation has better advantages in thermal comfort,and the daily power consumption of the air conditioning system under the control of this method can be reduced by 10.7%and 20.1%respectively compared with the thermal sensation feedback-based control method and the temperature set point-based control method.Finally,the online acquisition and learning of the characteristics of the personalized setting of the room temperature setting value of the users is another theoretical problem that worth studying to further improve the intelligent level of automatic room temperature control of air conditioning and the system's energy saving potential.In this dissertation,the machine learning theory is introduced into the online learning process of users' room temperature preference setting characteristics of air conditioning.An intelligent control method of room temperature preference setting of air conditioning is proposed based on reinforcement learning.The reinforcement learning algorithm of room temperature setting of air conditioners is trained and analyzed by using the above experimental data.The results show that the method can not only satisfy the thermal comfort of users,but also realize the efficient and energy-saving control of the air conditioning system.The research of this dissertation has important theoretical value and academic significance for solving the problems of human thermal sensation real-time perception,prediction and evaluation,and energy-saving optimization operation regulation and control of air conditioning system,especially for solving the disconnection between the optimization operation control of air conditioning system in public buildings and the engineering application of human(group)thermal sensation.It has important practical significance for energy saving and emission reduction to improve the thermal comfort of building environment and reduce the energy consumption of air conditioning system.