Research On The Temperature Control Of Blackbody Radiation Source Based On Neural Network With PID Algorithm

The blackbody radiation source can be used as a known intensity or known spectral distribution of heat source,and it can produce the standard radiation under a certain temperature.It is the key device for calibrating non-contact thermometer,such as infrared thermometer and photoelectric pyrometer in the process of calibration.The stability and uniformity of cavity of the blackbody radiation source directly affect the accuracy of all kinds of radiation thermometer calibration.Therefore,the temperature control of the blackbody radiation source is essential for calibrating.First of all,in this article,the dynamic characteristics of blackbody radiation source heating furnace is analyzed,according to the theory of heat transfer in the furnace,it is deduced the model structure of blackbody radiation source,and it is obtained its mathematical model by the step response identification method.Then,through theoretical analysis,the traditional PID controlling parameters are fixed,and it is analyzed by simulation that the characteristics of this temperature controlling algorithm of blackbody radiation are reasonable.Secondly,it introduces the basic theory and characteristics of the control strategy combining neural network with traditional PID,and it explains the advantages of the temperature control for blackbody radiation source system.The simulation results of blackbody radiation source temperature control system are studied by the MATLAB software,from aspects of the transition process,the control precision and anti-interference,to compare traditional PID control strategy with neural network PID control strategy in controlling performance.The simulation results show that the PID control method based on neural network can achieve better controlling quality for the black body radiation source temperature control.Finally,it establishes the software and hardware platform of the control system to realize the temperature control experiment of the blackbody radiation source with the PLC of RPC2000 series products,and real-time temperature is monitored and data is collected through display control screen,comparing the control performance of the traditional PID control strategy with the single neural network PID control.It shows with the experimental data that the PID control algorithm based on neural network has better quality controlling effect than the traditional PID control algorithm,such as high steady precision,less overshoot,short adjusting time.