Flame front identification and its effect on turbulent premixed flames topology at high pressure

Abstract

Image processing is of primary importance in the laser diagnostic on turbulent combustion, which can provide quantitative information, such as velocity field, intermediate species profile. Turbulent premixed flame front indicates the flame-turbulence interaction, can be decided from the OH-PLIF (Planar Laser Induced Fluorescence) technique due to the sharp increase of the OH distribution from unburned to burned region. In this paper, an adaptive threshold binarization method was proposed based on the local gray histogram of the OH-PLIF images when the signal-noise ratio is relatively low, i.e. turbulent flames at intensive turbulence and high pressure. The noise was eliminated by seed-mediated growth to obtain the legible flame front. Effect of different flame front identification methods, namely global binarization method, the canny operator of Matlab and the proposed adaptive threshold binarization method, on the flame structure parameters at various conditions was investigated. Results show that the flame fronts are seriously vague using the global binarization and the canny operator when the signal-noise ratio is low at intensive turbulence and high pressure, while continuous flame front can still be attracted by the proposed adaptive threshold binarization method. The turbulent flame front parameters from different methods are almost identical at weak turbulence and atmospheric pressure. While due to the noise introduced, the value of flame brush thickness, flame height and flame surface density from the proposed method is smaller than that of other two methods at high pressure. The adaptive threshold binarization method can obtain a better flame front identification at low signal-noise ratio conditions, results in reasonable premixed turbulent flame front parameters at intensive turbulence and high pressure.