连铸坯裂纹与偏析预测研究进展

doi:10.13228/j.boyuan.issn1005-4006.20220014

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Abstract Accurately predicting the defects such as cracks and center segregation of continuous casting strand and making a choice between offline cleaning and hot delivery are of great significance to stabilize the continuous casting production and improve the production quality. However, there are many factors affecting the quality of continuous casting strand in actual production. There are unpredictable disturbances in continuous casting production, and there is strong nonlinearity and coupling between production parameters, which makes the accurate prediction of the defects such as crack and central segregation of continuous casting strand very challenging. With the development of the continuous casting automation and computer technology, artificial intelligence has been paid more and more attention, among which machine learning has been gradually applied in the continuous casting production because of its strong nonlinear approximation ability. The research progress of the strand quality prediction at home and abroad are summarized from the aspects of the machine learning and expert system, and the advantages and disadvantages of various methods are analyzed and compared. Meanwhile, the quality prediction of continuous casting strand is prospected.

Key words： continuous casting billet crack center segregation quality prediction machine learning expert system

Received: 31 January 2022

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	Articles by authors
	ZOU Lei-lei
	HUANG Jun-xiong
	LI Quan-hui
	ZHANG Jiang-shan
	LIU Qing

Cite this article:

ZOU Lei-lei,HUANG Jun-xiong,LI Quan-hui等. Research progress on the crack and segregation prediction of continuous casting strand[J]. CONTINUOUS CASTING, 2022, 41(2): 2-9.

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http://www.chinamet.cn/Jweb_lz/EN/10.13228/j.boyuan.issn1005-4006.20220014 OR http://www.chinamet.cn/Jweb_lz/EN/Y2022/V41/I2/2

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