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Effect of a Preprocessing Method on the Inversion of OH* Chemiluminescence Images Acquired for Visualizing SNG Swirl-stabilized Flame Structure  

Ahn, Kwang Ho (Graduate School, Department of Building and Plant Engineering, Hanbat National University)
Song, Won Joon (Institute for Fusion Technology for Production, Hanbat National University)
Cha, Dong Jin (Department of Building and Plant Engineering, Hanbat National University)
Publication Information
Journal of the Korean Society of Combustion / v.20, no.1, 2015 , pp. 24-31 More about this Journal
Flame structure, which contains a useful information for studying combustion instability of the flame, is often quantitatively visualized with PLIF (planar laser-induced fluorescence) and/or chemiluminescence images. The latter, a line-integral of a flame property, needs to be preprocessed before being inverted, mainly due to its inherent noise and the axisymmetry assumption of the inversion. A preprocessing scheme utilizing multi-division of ROI (region of interest) of the chemiluminescence image is proposed. Its feasibility has been tested with OH PLIF and $OH^*$ chemiluminescence images of SNG (synthetic natural gas) swirl-stabilized flames taken from a model gas turbine combustor. It turns out that the multi-division technique outperforms two conventional ones: those are, one without preprocessing and the other with uni-division preprocessing, reconstructing the SNG flame structure much better than its two counterparts, when compared with the corresponding OH PLIF images. It is also found that the Canny edge detection algorithm used for detecting edges in the multi-division method works better than the Sobel algorithm does.
Flame structure; $OH^*$ chemiluminescence; Digital image preprocessing; Abel inversion; SNG;
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