Radiation Error Correction Of Forced Ventilation Temperature Sensor And The Design Of Software

As climate changes,the accuracy requirement of meteorology observation is increasing.The error measured by temperature sensors used in weather stations is required to be less than the order of 0.1 °C.When measuring atmospheric temperature,traditional temperature sensors absorb solar radiation,so that the measured temperature value is higher than the actual atmospheric temperature value.A radiation error close to 0.9 ° C or even higher can be observed.In order to achieve high-precision measurement requirements,it is necessary to design an efficient temperature sensor radiation shield to reduce the radiation error.In this paper,a two-layer forced ventilation temperature sensor radiation shield is designed,by using a computational fluid dynamics(CFD)method to simulate the temperature sensor based on the new radiation shield.The variation of temperature sensor radiation error under different environmental factors of solar radiation intensity,underlying surface reflectivity and air velocity is explored.The simulation results show that the solar radiation error has a monotonous relationship with the solar radiation intensity and the reflectivity of the underlying surface,and it has a monotonous decreasing relationship with the solar radiation intensity and the air velocity.A BP neural network is used to fit the CFD simulation value,and the radiation error equation is obtained,so that the radiation error of the forced ventilation temperature sensor under any environmental factors such as air velocity,underlying surface reflectivity and solar radiation intensity can be obtained.The results show that the absolute error of the CFD simulation value and the predicted value fitted in the BP neural network is less than 0.0025 °C,and the measurement accuracy of the temperature sensor has been remarkably improved.In order to query historical temperature data conveniently,this paper designs a historical temperature query and correction software,the software uses Bootstrap and AngularJS as the front-end development framework,and Spring MVC as the background development framework.The website can realize the functions of meteorological station information management,historical temperature data management,real-time meteorological data query,etc.At the same time,the user can also query the radiation error value under different environmental factors and correct the data.In this paper,the historical temperature data management module realizes the paid use of meteorological sensor data,realizes the profit of software through charging fees,and then has certain funds to study more types of sensors,obtain more meteorological data and store it in software for users to use,forming a positive effect.