A novel 3-D temperature field reconstruction method is proposed in this paper, which is based on multiwavelength thermometry and Hopfield neural network computed tomography. A mathematical model of multi-wavelength thermometry is founded, and a neural network algorithm based on multiobjective optimization is developed. Through computer simulation and comparison with the algebraic reconstruction technique (ART) and the filter back-projection algorithm (FBP), the reconstruction result of the new method is discussed in detail. The study shows that the new method always gives the best reconstruction results. At last, temperature distribution of a section of four peaks candle flame is reconstructed with this novel method.
© 2005 Chinese Optics Letters
(100.3010) Image processing : Image reconstruction techniques
(110.6960) Imaging systems : Tomography
(120.6780) Instrumentation, measurement, and metrology : Temperature
(200.4260) Optics in computing : Neural networks
(300.6170) Spectroscopy : Spectra
Xiong Wan, Yiqing Gao, and Yuanmei Wang, "3-D flame temperature field reconstruction with multiobjective neural network," Chin. Opt. Lett. 1, 78-81 (2003)