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

doi:10.13700/j.bh.1001-5965.2019.0337

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

黄兴^{1, 2},
齐宏^{1, 2, ,},
牛志田^{1, 2},
任亚涛^{1, 2},
阮立明^{1, 2}

1.
哈尔滨工业大学能源科学与工程学院, 哈尔滨 150001
2.
空天热物理工业和信息化部重点实验室, 哈尔滨 150001

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
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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

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

HUANG Xing^{1, 2},
QI Hong^{1, 2
, ,},
NIU Zhitian^{1, 2},
REN Yatao^{1, 2},
RUAN Liming^{1, 2}

1.
School of Energy Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
2.
Key Laboratory of Aerospace Thermophysics, Ministry of Industry and Information Technology, Harbin 150001, China

Funds:

National Natural Science Foundation of China 51976044

China Postdoctoral Science Foundation 2018M6300351

More Information

Corresponding author: QI Hong, E-mail: qihong@hit.edu.cn

摘要

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。
- 光场成像 /
- 温度测量 /
- 燃烧诊断 /
- 反问题 /
- Landweber算法
Abstract:
Light field imaging technology is an emerging non-contact temperature measurement technology. Aiming at the important role of light field imaging reconstruction algorithm for flame temperature field measurement, the flame temperature field reconstruction algorithm based on light field imaging was studied. A flame temperature field reconstruction method based on the light-field imaging technique is proposed, the generalized sourced multi-flux method is used as the calculation method of direct problem, and Landweber algorithm is applied to reconstruct the 3D temperature field of absorbing and scattering flame based on the flame light-field imaging model. The Least-Square QR (LSQR) decomposition algorithm is also introduced to our study as a comparison to verify the performance of Landweber algorithm. Effect of measurement errors on the computational accuracy is studied. The reconstruction results demonstrate that the temperature field can be reconstructed reasonably by these two methods, and even with 5% measurement error, the mean reconstruction relative errors are 0.91% and 0.92% respectively, which are acceptable. The comparative results show that the Landweber algorithm has the similar calculation precision as LSQR algorithm, but the calculation time of the Landweber algorithm is one tenth of that of LSQR algorithm, and thus the Landweber algorithm is much more efficient than LSQR algorithm.
- light-field imaging /
- temperature measurement /
- combustion diagnostics /
- inverse problems /
- Landweber algorithm

HTML全文

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

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

图 3 模拟光场图像

Figure 3. Simulated light-field image

下载: 全尺寸图片幻灯片

图 4 LSQR算法三维温度场重建结果

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

下载: 全尺寸图片幻灯片

图 5 Landweber算法三维温度场重建结果

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

下载: 全尺寸图片幻灯片

图 6 LSQR算法重建相对误差分布

Figure 6. Reconstruction relative error distribution of LSQR algorithm

下载: 全尺寸图片幻灯片

图 7 Landweber算法重建相对误差分布

Figure 7. Reconstruction relative error distribution of Landweber algorithm

下载: 全尺寸图片幻灯片

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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