Relative Entropy Regularized TDLAS Tomography for Robust Temperature Imaging

Abstract

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 wellestablished 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.

Cost-Effective Quasi-Parallel Sensing Instrumentation for Industrial Chemical Species Tomography

“…Fig. 12 shows the resulting image of H2O concentration reconstructed using the Simultaneous Algebraic Reconstruction Technique (SART) with detailed procedures illustrated in our previous research [32]. The reconstructed image exhibits good quality with few artefacts, but also agrees well with the phantom in terms of the location of the high H2O concentration region relative to room air.…”

Calibration-free wavelength modulation spectroscopy based on even-order harmonics

“…9 (a) indicates similar results as those using the noise-free data. As the temperature sensitivities of the chosen H2O transitions decrease as the temperature increases [22,26], the retrieved temperature suffers from more significant fluctuations, indicated by the larger values of RSDs shown in Fig. 9 (b), at higher temperatures.…”

CSTNet: A Dual-Branch Convolutional Neural Network for Imaging of Reactive Flows Using Chemical Species Tomography

“…5. More details of the optics, e.g., lasers and detectors, electronics, e.g., data acquisition and signal processing system, and the parameter settings in wavelength modulation spectroscopy have been described in [39].…”