Relative Entropy Regularized TDLAS Tomography for Robust Temperature Imaging
Relative Entropy Regularized TDLAS Tomography for Robust Temperature Imaging
复制标题
DOI：
10.1109/tim.2020.3037950
复制
发表时间：
2021-01-01
影响因子：
5.6
通讯作者：
Liu, Chang
中科院分区：
文献类型：
--
作者：
Bao, Yong;Zhang, Rui;Liu, Chang
可调谐二极管激光吸收光谱（TDLAS）层析成像技术已广泛应用于现场燃烧诊断，可产生物质浓度和温度的图像。温度图像一般由两次光谱跃迁重建的吸光度分布得到，即双线测温。然而，层析数据反演固有的不适定性导致在每个重建的吸光度分布中存在噪声。这些噪声效应传播到吸光度比，并在检索的温度图像中产生伪影。为了解决这个问题，我们开发了一种新的算法，我们称之为相对熵层析重建（RETRO），用于TDLAS断层扫描。引入了一种相对熵正则化方法，用于联合重建双线吸光度分布的高保真温度图像检索。我们已经进行了数值模拟和概念验证实验来验证所提出的算法。与已有的同步代数重建技术（SART）相比，RETRO算法显著提高了层析温度图像的质量，对TDLAS层析测量噪声具有良好的鲁棒性。RETRO为TDLAS断层成像的工业现场应用提供了巨大的潜力，在这些应用中，在非常恶劣的环境中进行测量是很常见的。
Tunable diode laser absorption spectroscopy (TDLAS) tomography has been widely used for in situ combustion diagnostics, yielding images of both species concentration and temperature. The temperature image is generally obtained from the reconstructed absorbance distributions for two spectral transitions, i.e., two-line thermometry. However, the inherently ill-posed nature of tomographic data inversion leads to noise in each of the reconstructed absorbance distributions. These noise effects propagate into the absorbance ratio and generate artifacts in the retrieved temperature image. To address this problem, we have developed a novel algorithm, which we call Relative Entropy Tomographic RecOnstruction (RETRO), for TDLAS tomography. A relative entropy regularization is introduced for high-fidelity temperature image retrieval from jointly reconstructed two-line absorbance distributions. We have carried out numerical simulations and proof-of-concept experiments to validate the proposed algorithm. Compared with the well-established simultaneous algebraic reconstruction technique (SART), the RETRO algorithm significantly improves the quality of the tomographic temperature images, exhibiting excellent robustness against TDLAS tomographic measurement noise. RETRO offers great potential for industrial field applications of TDLAS tomography, where it is common for measurements to be performed in very harsh environments.