Abstract
The unknown emissivity still poses a significant challenge in the data processing of Multispectral radiation thermometry (MRT). In order to achieve global optimal solution with fast convergence speed and strong robustness, a systematic comparative analysis of particle swarm optimization (PSO) and simulated annealing (SA) algorithms in the application in MRT is presented in this paper. The simulations of six hypothetical emissivity models were compared, and the results indicate that the PSO algorithm is superior to the SA algorithm in accuracy, efficiency and stability. The measured data of the surface temperature of rocket motor nozzle is simulated by the PSO algorithm, the maximum absolute error and the maximum relative error are 16.27 K and 0.65%, and the calculation time is less than 0.3 s. The superior performance of the PSO algorithm indicates that it can be well used in data processing for accurate temperature measurement in MRT, and the method proposed in this paper can be extended to other multispectral systems and applied to various industrial processes under high temperature conditions.
Funder
Program for Innovative Research Team (in Science and Technology) in University of Henan Province
Key Scientific Research Project of Colleges and Universities in Henan Province
Natural Science Foundation of Henan Province
Innovation Scientists and Technicians Troop Construction Projects of Henan Province
National Natural Science Foundation of China
Subject
Atomic and Molecular Physics, and Optics