Optimized CT-TDLAS reconstruction performance evaluation of least squares with the polynomial-fitting method

Abstract

Computed tomography-tunable diode laser absorption spectroscopy (CT-TDLAS) has been widely used in the diagnosis of the combustion flow field. Several optimized CT reconstruction algorithms such as iteration methods, transformation methods, and nonlinear least squares were applied. Considering the industrial application background, the performances of algebraic iteration reconstruction with the simultaneous algebra reconstruction technique (SART), Tikhonov regularization, and least squares with the polynomial fitting method were discussed in this study. For the mentioned algorithm, identical simulated reconstruction parameters that contained 32-path laser structures, assumed temperature distribution, and absorption databases were adopted to evaluate the reconstruction performance including accuracy, efficiency, and measurement of environment applicability. In this study, different CT reconstruction algorithms were also used to calculate the temperature distribution of the Bunsen burner flame. The different reconstruction results were compared with thermocouple detection data. With the theoretically simulated and experimental analysis, the least squares with the polynomial fitting technique has advantages in reconstruction accuracy, calculation efficiency, and laser path applicability for the measurement condition. It will be helpful in enhancing CT-TDLAS technique development.