Chinese Optics Letters, Volume. 1, Issue 2, 0278(2003)

3-D flame temperature field reconstruction with multiobjective neural network

Xiong Wan1,2、*, Yiqing Gao2, and Yuanmei Wang2
Author Affiliations
  • 1Institute of Automation of Nanjing University of Aeronautics and Astronautics, Nanjing 210016
  • 2Department of Test and Control Engineering, Nanchang Institute of Aeronautical Technology, Nanchang 330034
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    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.

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    Xiong Wan, Yiqing Gao, Yuanmei Wang. 3-D flame temperature field reconstruction with multiobjective neural network[J]. Chinese Optics Letters, 2003, 1(2): 0278

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    Paper Information

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    Received: Aug. 21, 2002

    Accepted: --

    Published Online: Jun. 6, 2006

    The Author Email: Xiong Wan (wanxiong1@163.net)

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