Research progress of sinter tail sectional image based on computer vision

The section of the tail of sintering machine can directly reflect the rich information of sintering process control and sinter quality. How to use computer vision technology to extract the characteristics of the tail section and realize the accurate prediction and control of sinter quality is one of the key research contents of intelligent sintering. The image preprocessing methods such as denoising, segmentation and feature extraction of sinter tail section images were compared and analyzed comprehensively. Then the application situation of the image analysis technique for sintering machine tail section in the field of sinter quality prediction and control was analyzed from the aspects of FeO content in sintering ore, sintering end point, drum strength, distribution uniformity, sinter mixture moisture, etc. In addition, taking the prediction for FeO content in sintering ore as an example, the development and evolution rules of the study on sinter tail section image based on computer vision were revealed. The disadvantages of the current research and the development trend in the future were also pointed out.