There are complex non-linear relationships between various process parameters and control targets in con-tinuous casting process.Traditional methods,such as numerical simulation and laboratory experiment,cannot meet the requirement of efficient production of enterprises due to their poor optimization efficiency.At present,machine learning has been widely used in the abnormal prediction,quality detection and process optimization with the aims to improve productivity and slab quality,as well as accelerate the development of new technologies and digital transfor-mation in continuous casting.Current advancements of machine learning application in the predicted strategy,fea-ture extraction and model construction in various stages of continuous casting process are summarized.The results show that the machine learning offers higher predictive accuracy and better generalization ability in continuous cast-ing production compared with the traditional methods.It also can achieve fine and intelligent control of continuous casting process after building corresponding models for different prediction targets.Meanwhile,feature research di-rections for machine learning application in continuous casting production are also proposed from three aspects of sample distribution,data quality,and model development/application.This outlook aims to provide valuable refer-ences for the intelligent advancement of continuous casting.
NETL
NSTL
万方数据
