Effects of hydrogen and primary air in a commercial partially-premixed atmospheric gas burner by means of optical and supervised machine learning techniques

In order to ascertain the effects of the hydrogen addition and the primary air-fuel ratio on burner performance and emissions, we conduct tests on a commercial atmospheric gas burner using pure methane and a blend of hydrogen/methane. Relevant statistical image features are extracted from a UV–VIS camera equipped with narrow-band optical filters. Radical image results agrees with spectrometric data, showing the relevance of the OH* intensity radiation coming from the outer non-premixed zone. The double-cone flame structure is evident, showing a growing secondary non-premixed cone as the primary air-fuel ratio is decreased. In addition, the direct relationship found between flame radical imaging features and NOx emissions has been used to develop a predictive model by integrating classification techniques and neural networks. The research confirms UV–VIS chemiluminescence imaging techniques as powerful tools aimed at combustion monitoring, with huge prospects of being integrated within advanced emission control techniques for commercial burners