A new monitoring method for the blocking time of the taphole of blast furnace using molten iron flow images

When to block the taphole is a concern in blast furnace ironmaking process. Currently, the blocking time of the taphole mainly depends on expertise, causing poor reliability of the blocking operation. Therefore, this paper proposes a new method to intelligently determine the blocking time using molten iron flow images. Firstly, a monitoring system is designed to obtain molten iron flow images at the taphole. Secondly, the blocking time monitoring problem is transformed into a classification problem of molten iron image to obtain tapping stages, and a novel image classification module, which further promotes the network’s representational ability by merging three feature extraction mechanisms in parallel, is proposed to accurately classify the images and obtain the tapping stages. Finally, a categorical correction model and a blocking time calculation model are constructed to obtain an accurate blocking time. Experimental results show that the proposed method can accurately monitor the taphole’s blocking time. •A new monitoring method is proposed to realize the intelligent monitoring of the taphole blocking time in ironmaking process.•The blocking time monitoring problem is transformed into a classification problem of tapping stages and a statistical prediction problem.•A novel deep image classification module is proposed to classify molten iron flow images and obtain tapping stages.•According to the tapping stages, a categorical correction model and a remaining blocking time calculation model are constructed to obtain the accurate taphole blocking time.