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基于光场成像技术的散射性火焰温度场重建

黄兴 齐宏 牛志田 任亚涛 阮立明

黄兴, 齐宏, 牛志田, 等 . 基于光场成像技术的散射性火焰温度场重建[J]. 北京航空航天大学学报, 2020, 46(5): 952-959. doi: 10.13700/j.bh.1001-5965.2019.0337
引用本文: 黄兴, 齐宏, 牛志田, 等 . 基于光场成像技术的散射性火焰温度场重建[J]. 北京航空航天大学学报, 2020, 46(5): 952-959. doi: 10.13700/j.bh.1001-5965.2019.0337
HUANG Xing, QI Hong, NIU Zhitian, et al. Temperature field reconstruction of scattering flame based on light-field imaging[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(5): 952-959. doi: 10.13700/j.bh.1001-5965.2019.0337(in Chinese)
Citation: HUANG Xing, QI Hong, NIU Zhitian, et al. Temperature field reconstruction of scattering flame based on light-field imaging[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(5): 952-959. doi: 10.13700/j.bh.1001-5965.2019.0337(in Chinese)

基于光场成像技术的散射性火焰温度场重建

doi: 10.13700/j.bh.1001-5965.2019.0337
基金项目: 

国家自然科学基金 51976044

中国博士后科学基金 2018M6300351

详细信息
    作者简介:

    黄兴  男, 博士研究生。主要研究方向:高温发光火焰温度场及辐射物性测量

    齐宏  男, 博士, 教授, 博士生导师。主要研究方向:热辐射传输与耦合换热、高温弥散颗粒辐射物性及温度测量、辐射传输逆问题及智能优化算法等

    通讯作者:

    齐宏, E-mail: qihong@hit.edu.cn

  • 中图分类号: V435+.12;TK121

Temperature field reconstruction of scattering flame based on light-field imaging

Funds: 

National Natural Science Foundation of China 51976044

China Postdoctoral Science Foundation 2018M6300351

More Information
  • 摘要:

    光场成像是一项新兴的非接触式测温技术,针对传统辐射成像温度场重构效率低的问题,开展了基于光场成像的散射性火焰温度场重建研究。在火焰光场成像模型的基础上,以广义源项多流法为正问题模型,利用Landweber算法重构吸收散射性火焰的三维温度场,同时引入最小二乘QR(LSQR)分解算法作为对比以衡量Landweber算法的性能。分析了测量误差对于重建精度的影响,重建结果表明,即使在添加5%测量误差的情况下温度场的平均重建相对误差也仅为0.91%和0.92%,重建结果仍然是合理的。Landweber算法和LSQR算法具有相当的计算精度,但Landweber算法的计算时间是LSQR算法的1/10,其计算效率明显优于LSQR算法。

     

  • 图 1  光场成像的射线追踪示意图

    Figure 1.  Schematic diagram of ray tracing of light-field imaging

    图 2  基于光场成像与Landweber算法的火焰温度场重建流程

    Figure 2.  Flowchart of flame temperature field reconstruction based on light-field imaging and Landweber algorithm

    图 3  模拟光场图像

    Figure 3.  Simulated light-field image

    图 4  LSQR算法三维温度场重建结果

    Figure 4.  Reconstructed 3D temperature field distribution using LSQR algorithm

    图 5  Landweber算法三维温度场重建结果

    Figure 5.  Reconstructed 3D temperature field distribution using Landweber algorithm

    图 6  LSQR算法重建相对误差分布

    Figure 6.  Reconstruction relative error distribution of LSQR algorithm

    图 7  Landweber算法重建相对误差分布

    Figure 7.  Reconstruction relative error distribution of Landweber algorithm

    表  1  LSQR算法与Landweber算法计算结果对比

    Table  1.   Comparison of calculation results between LSQR algorithm and Landweber algorithm

    算法 测量误差/% 平均重建相对误差/% 计算时间/s
    LSQR 1 0.21 23.13
    3 0.71 24.31
    5 0.91 22.87
    Landweber 1 0.22 2.50
    3 0.71 2.50
    5 0.92 2.50
    下载: 导出CSV
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  • 被引次数: 0
出版历程
  • 收稿日期:  2019-06-28
  • 录用日期:  2019-08-30
  • 网络出版日期:  2020-05-20

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