Summary of research on flame 3D reconstruction based on computed tomography of chemiluminescence technology
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摘要: 燃烧过程具有三维、高温、湍流、非稳态等特性，其精确测量存在一定的难度，一直是国内外研究的热点。化学发光计算断层成像（CTC）技术将化学发光技术和计算机断层成像（CT）技术相结合，通过直接拍摄不同角度的火焰图像，利用重构算法进行重建，可以快速准确地实现火焰三维结构的精细刻画。CTC系统以火焰的自发光作为光源，因此不需要额外的光源设备，这使得该系统具有容易搭建、可在复杂环境下实现等优势，可以用于高温、湍流火焰的实时测量，对于研究复杂燃烧流场、提高燃烧效率有着十分重要的意义。本文首先介绍了CTC技术的基本原理，然后从成像模型、重构算法、实验方法和应用方向4个方面介绍了CTC技术在火焰重构方向的研究进展，最后讨论了CTC技术的发展趋势。Abstract: Due to the characteristics of combustion such as three-dimension, high temperature, turbulence, and unsteady state accurate measurement of the combustion is difficult and is a hot research topic. Computed Tomography of Chemiluminescence (CTC) combines the chemiluminescence and CT technology. By directly shooting flame images from different angles and using reconstruction algorithms to reconstruct the flame, a fine description of the three-dimensional structure of the flame can be achieved quickly and accurately. The self-luminescence of the flame is used in the CTC as the light source, so there is no additional light source equipment required, which makes the system easy to build and can be implemented in a complex environment. These advantages enable the CTC technology to be used for real-time measurement of high temperature and turbulent flames, which is of great significance for studying complex combustion flow fields and improving combustion efficiency. In this paper, the basic principles of the CTC technology are introduced firstly, and then the research progress of the CTC technology in the direction of 3D reconstruction of flame is introduced in four aspects: the imaging model, the reconstruction algorithm, the experimental equipment and its application. Finally, the development trend of the CTC technology is discussed.
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表 1 CTC重构算法的发展
Table 1. Development of CTC reconstruction algorithms
参考文献 成像模型 重建维度 改进方式及成果 [47] 线性成像模型 二维切片叠加 改进权系数矩阵计算方法，加快了重建速度 [49] 线性成像模型 二维切片叠加 将问题转化为二值问题，减少了投影角数量 [50] 线性成像模型 二维切片叠加 提出了使用退火模拟算法求解二元函数，提高了解决二元问题的效率 [24] 线性成像模型 三维重建 首次提出直接三维重建方式，提高了重建精度 [51] 线性成像模型 三维重建 提出了基于熵最大化并结合MENT的直接三维重建算法，减少了重建误差及计算时间 [52] 线性成像模型 三维重建 基于Mojette变换理论，研究了在小角度情况下的重建 [53-54] 线性成像模型 三维重建 提出了FBP算法分别与ART算法和SART算法结合的LFBP−ART和
LFBP−SART算法，提高了重建精度[30] 线性成像模型 三维重建 提出基于光线追踪的成像模型，减少了投影数量 [36] 点扩散函数成像模型 三维重建 提出使用点扩散函数成像模型，引入正则化条件，提高了重建精度 [57] 点扩散函数成像模型 三维重建 提出了点扩散函数的简化模型 [59-60] 点扩散函数成像模型 三维重建 结合相机的缺陷改进了成像模型 [61] 点扩散函数成像模型 三维重建 考虑了火焰自吸收问题，改善了成像过程中信号衰减的问题 
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表 2 不同实验方法的优缺点
Table 2. Advantages and disadvantages of different experimental methods
实验方法 优点 缺点 直接相机拍摄法 实验布置简单；实验设备相对容易获得 多台相机的成本高；能获得的拍摄角度较少 相机 + 反射镜法 减少了相机的使用数量，降低了硬件成本 减少的数量有限，只能降低一半的相机数量；反射镜会降低拍摄精度且反射镜角度不容易精确获得 相机 + 光线内窥镜法 进一步减少相机的使用数量，降低成本；光纤内窥镜体积较小，相同空间内可以布置更多的投影角度 光纤束会造成光信号的损失；拍摄得到的图像信噪比相对较差
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