The Design of Temperature Monitoring and Cooling Control System Considering Error Compensation

Due to the development of science and technology, more and more data centers are built. However, the equipment of data center is more demanding to the ambient temperature. Air conditioning is an important temperature and humidity control equipment. Outside air conditioner is an important component. Outside air conditioning failure causes system failure, which affects the normal operation of data center. Therefore, it is very necessary to monitor and reduce the temperature of air-conditioning units outside the data center. Firstly, a temperature error compensation model of infrared thermal imager based on neural network model is put forward. The measured temperature is corrected by introducing ambient temperature and position parameters to improve the temperature monitoring accuracy, and the control system of air-conditioning units outside temperature is designed. The proposed error compensation method and control system are developed on LabView platform. Experiments show that the proposed temperature compensation method can reduce the temperature measurement error of the imager to about 1.5 ∼C, while the cooling control system can control the spray angle error within 0.5 ∼C, and spraying water can significantly reduce the outside temperature of the air conditioner to the desired temperature. Neural network temperature compensation can effectively improve the accuracy of external machine temperature monitoring, and automatic temperature control can replace the original manual cooling mode to reduce the work intensity of human.