Abstract The core of multi-spectral radiation thermometry lies in determining the object’s emissivity. However, existing methods generally suffer from issues such as low accuracy and poor applicability. This paper establishes a relevant mathematical model and constraint conditions based on Planck’s radiation law and multi-objective constraint optimization theory. By integrating the particle swarm optimization (PSO) and JAYA algorithms, the proposed approach addresses the tendency of PSO to get trapped in local optima and the slower convergence speed of the JAYA algorithm. Simulation experiments conducted under four different wavelength and emissivity models at a true temperature of 2,000 K demonstrate that the PSO-JAYA method achieves a retrieval error of only 0.8 % and significantly improves retrieval speed. The method exhibits notable advantages in both retrieval accuracy and efficiency, confirming its reliability for practical applications.
Ma et al. (Thu,) studied this question.