烧结系统智能制造与大数据技术应用探讨

doi:10.13228/j.boyuan.issn0449-749x.20210088

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Abstract In order to improve the intelligent manufacturing level of the sintering process, the research progress about the sintering system model in recent decades was systematically summarized. For the current problems in the models of sintering endpoint prediction, composition and quality prediction of sinter ore, and batching optimization, the prediction and optimization of the parameter in the sintering system were investigated by using big data, integrated learning and deep learning. Accordingly, the remarkable results in terms of the improvement in the prediction accuracy and the generalization ability were also emphatically introduced. Moreover, based on the parameter prediction model mentioned above, the hardware and software structure design methods of the parameter prediction and optimization system for on-site application were put forward. Finally, starting from the needs of the iron and steel industry, the point of view, the further integration of advanced information technology and industrial automation equipment was an important way to improve the level of intelligent manufacturing of sintering systems was analyzed, and the research direction and application prospects of big data and artificial intelligence technology in the sintering were also discussed.

Key words： sintering predictive model big data integrated learning deep learning

Received: 19 February 2021

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http://www.chinamet.cn/Jweb_gt/EN/10.13228/j.boyuan.issn0449-749x.20210088 OR http://www.chinamet.cn/Jweb_gt/EN/Y2021/V56/I10/54

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