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Recognition of burning state based on flame images has been an important issue in sintering process of rotary kiln. Existing methods usually adopt techniques of image segmentation, pattern recognition and machine learning, which have high demands on the quality of samples and computational power. It is challenging to the on-line recognition of the burning state, which is essential in realtime control...
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