Combustion Diagnostics by Calibrated Radiation Sensing and Spectral Estimation

Optimization of combustion processes holds the promise of maximizing energy efficiency, at the same time lowering fuel consumption and residual gases emissions. In this context, the current common operation setting in combustion processes could be improved by the introduction of passive optical sensors, which can be located close the flame, thus eliminating the inherent transport delay in current setups that only infer the combustion quality by measuring residual gases emissions. However, there is a tradeoff for flame detection between spatial-spectral resolutions, depending on the optical sensor scheme. In this paper, we present the fundamentals to avoid this constraint, obtaining a combined high spectral and spatial resolution measurement suitable for combustion diagnostics and control. The core of this proposal is to use the flame images from a low-spectral resolution charge-coupled device camera, combined with a spectral recovery method. This method is based on the off-line samples measured on the continuous component of flame spectra, providing a set of vector basis to estimate a calibrated flame spectra at each pixel. The results of the spectral recovery process verify the suitability of the method in terms of goodness-of-fit coefficient and root mean square error metrics, enabling hyper-spectral measurements based on the combination of different optical sensors. Then, continuous estimated spectra along the flame are used to calculate the energy transfer released by radiation, useful for combustion diagnostics.