铸造技术2025，Vol.46Issue(10)：964-972,9.DOI:10.16410/j.issn1000-8365.2025.5117
数据驱动结晶器液位波动与卷渣缺陷相关性研究
Data-driven Correlation Analysis of Mold Level Fluctuation and Slag Entrapment Defects
摘要
Abstract
In modern interstitial-free(IF)steel continuous casting processes,the stability of the mold level plays a critical role in determining slab quality.Excessive fluctuations may cause slag entrapment into molten steel,resulting in inclusion defects that degrade the purity and final mechanical properties of the steel.While traditional process monitoring primarily depends on physical experiments and finite element simulations,the advancement of industrial data acquisition technologies has enabled data-driven approaches to demonstrate significant potential for process optimization.Industrial IF steel casting operations involving the collection of mold level fluctuation data,slag entrapment records,and associated process parameters were investigated.Through integrated statistical analysis,time series characterization and machine learning techniques,the intrinsic relationship between mold-level fluctuation patterns and slag entrapment mechanisms was systematically explored,and corresponding control strategies were proposed.The results demonstrate significant correlations between the characteristic parameters of level fluctuations and slag entrapment defects.The implementation of optimized control strategies effectively reduces the probability of inclusion formation.关键词
IF钢/连铸工艺/结晶器液位波动/卷渣缺陷/数据驱动分析Key words
interstitial-free steel/continuous casting process/mold level fluctuation/slag entrapment defect/data-driven analysis分类
金属材料引用本文复制引用
陆志豪,赵晨光,马永东,陈宇,尚世震,李博洋,贾吉祥..数据驱动结晶器液位波动与卷渣缺陷相关性研究[J].铸造技术,2025,46(10):964-972,9.基金项目
辽宁省技术攻关计划(2024JH2/102600056) （2024JH2/102600056）
