Hyperspectral image reconstruction from colored natural flame luminosity imaging in a tri-fuel optical engine

The detection of chemiluminescence from various radicals and molecules in a hydrocarbon flame can provide valuable information on the rate of local heat release, combustion stability, and combustion completeness. In this study, chemiluminescence from the combustion process is detected using a high-speed color camera within the broadband spectrum of visible light. Whereon, a novel hyperspectral reconstruction approach based on the physically plausible spectral reconstruction (PPSR) is employed to reconstruct the spectral chemiluminescence signals from 400 to 700 nm with a resolution of 10 nm to provide 31 different spectral channels. The reconstructed key chemiluminescence signals (e.g., CH*, CH(2)O*, C(2)*, and CO(2)*) from the color images are further analyzed to characterize the chemical kinetics and combustion processes under engine conditions. The spectral chemiluminescence evolution with engine crank angle is identified to comprehend the effect of H(2) fraction on flame characteristics and combustion kinetics. Additionally, in this study, a detailed kinetic mechanism is adopted to deepen the theoretical understanding and describe the spectral chemiluminescence from H(2)/CH(4) and H(2)/CH(4)/n-dodecane flames at relevant conditions for various species including OH*, CH*, C(2)*, and CO(2)*. The results indicate that the PPSR is an adequately reliable approach to reconstructing spectral wavelengths based on chemiluminescence signals from the color images, which can potentially provide qualitative information about the evolution of various species during combustion. Here, the reconstructed chemiluminescence images show less than 1% errors compared to the raw images in red, green, and blue channels. Furthermore, the reconstructed chemiluminescence trends of CH*, CH(2)O*, C(2)*, and CO(2)* show a good agreement with the detailed kinetics 0D simulation.