2020/07/13 by Yong Bao, Bao, Yong, Rui Zhang +11
Biochemistry, Genetics and Molecular Biology · Chemistry · Engineering · #Data Analysis #FOS: Electrical engineering #FOS: Physical sciences #Image and Video Processing (eess.IV) #Instrumentation and Detectors (physics.ins-det) #Photoacoustic and Ultrasonic Imaging #Spectroscopy Techniques in Biomedical and Chemical Research #Spectroscopy and Laser Applications #Statistics and Probability (physics.data-an) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2007.06416
openalex publication_date 2020/07/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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 artefacts 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 regularisation 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.