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Investigation on High-Pressure Methane Jet Turbulent Combustion Flame Image Processing Method Based on Deep Learning |
DOI:10.13949/j.cnki.nrjgc.2022.04.003 |
Key Words:deep learning image segmentation methane high-pressure jet turbulent flame |
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Abstract:Based on a constant volume combustion chamber(CVC), an optical experiments of high-pressure nature gas (methane) jet combustion was carried out, and the flame image processing was completed by the deep learning method and the edge detection algorithm, respectively. The comparative results showed that because there were both gas jet and flame in these images which had many targets with great difference, the edge detection algorithm could not clearly identify the gas jet and the flame, so it is suitable for single target image processing. The deep learning method could gain the flame contour, and further effectively obtain the macroscopic property of the jet turbulent flame such as the jet turbulent flame propagation distance and flame propagation velocity, so it is suitable for multi-target image processing. The results based on deep learning image processing method show that when the high-pressure methane jet meets the premixed fireball, the flame speed rapidly increases from the initial laminar speed (<3 m/s) up to greater speed with the maximum flame speed of more than 300 m/s, which forms the turbulent flame. The turbulent flame penetrates forward along the jet direction and the area of the jet flame increases. The maximum flame speed linearly decreases as the interval between the jet and the spark ignition. |
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