Multi-wavelength radiometric thermometry data processing algorithm based on the BFGS algorithm

Multi-wavelength radiometric thermometry has a wide application prospect in many fields. However, due to unknown emissivity, the data processing algorithm remains a difficult problem. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is proposed to inverse true temperature and spectral emissivity without assuming the emissivity model. The BFGS algorithm can automatically identify the emissivity models of different trends. These simulation results show that given different initial emissivity has no significant influence on the inverse temperature and emissivity. Then, we select 0.5 as the initial emissivity and carry out the simulation experiments at 800 and 900 K, respectively. The maximum absolute error of temperature is less than 3.5 K and the computation time is less than 0.2 s. Thus, the algorithm has high precision and efficiency. Finally, the verification experiment indicates that the BFGS algorithm is effective and reliable. The proposed method can be applied to real-time temperature measurement in many industrial processes.