The Application Study Of Blackbody Radiation Source Temperature Control System Based On PSO-BP Algorithm

Blackbody radiation source is used to calibrate the radiation temperature measurement instrument in the field of temperature measurement technology,and it is particularly important for the high precision control of temperature.At present,the PID control algorithm for blackbody has been used commonly.Because blackbody is used in different occasions and temperature control requirements continue to improve,the traditional PID control algorithm has been unable to fully meet the need.Therefore,this paper studies and analyzes the temperature control system of blackbody radiation source,and improves its temperature control to meet higher practical application requirements.According to the requirements of the subject,the temperature control system is designed to control surface source and cavity type blackbody respectively.In this paper,the refrigeration control object is a gallium point source blackbody with a diameter of 10 mm and a thickness of 4mm.It is greatly affected by the environment and other factors for small volume,so it is difficult to control its temperature.PID control is used in the most of the existing controllers market,which is difficult to meet the requirements of the research.So this paper redesigned a temperature controller based on the single-chip Arduino mega 2560,and improved the temperature control algorithm to meet the requirements of temperature control.And in the control of blackbody heating mode of cavity,the traditional PID controller is difficult to achieve satisfactory control effect in terms of control precision and stability.This paper fully analyzes the working principle of the blackbody radiation source and improving the accuracy,and combines the particle swarm BP neural network PID algorithm is applied to the blackbody temperature control system.First,the paper introduces blackbody of surface source with the basic structure and performance requirements,and study and analyze the heating and cooling process of the system.The system parameters are identified by MATLAB software,and finally the mathematical model of heating and cooling of the blackbody radiation source is obtained.Secondly,the principle is introduced for particle swarm BP neural network PID algorithm,and the simulation results of are compared and analyzed with other algorithm through Matlab/Simulink.The simulation results show that the PID algorithm based on particle swarm BP neural network has the advantages of small overshoot,high precision and short adjustment time.Finally,the hardware platform of the temperature control system is designed and built.The Arduino mega 2560 single-board computer is used as the temperature controller.The PID control algorithm of particle swarm BP neural network is applied to the blackbody temperature control system through offline training,and the effect is compared with the traditional PID control of standard blackbody.The particle swarm BP neural network PID algorithm has the advantages of small overshoot,high precision and short adjustment time compared with the traditional PID algorithm,which improves the temperature control quality of blackbody.