ELECTROMAGNETIC METALLURGY DIGITAL SYSTEM BASED ON BIG DATA AND ARTIFICIAL INTELLIGENCE
The optimization of process variables in electromagnetic metallurgy and continuous casting technology is an important means for enterprises to improve the quality of continuous casting billets.However,the explanation of the mechanism of continuous casting process and the adjustment methods of process variables by enterprises are seriously lagging behind production.Therefore,this article proposes the integration of multiple technologies such as numerical simulation,computer vision,and big data mining to achieve visualization of multiple physical fields in the continuous casting process,automatic identification and intelligent detection of continuous casting billet quality,and coupling optimization of electromagnetic metallurgy technology and continuous casting process variables.The electromagnetic metallurgy digital system has the preliminary ability to visualize multiple physical fields such as flow field,temperature field,liquid phase volume fraction,solute field,inclusion distribution,and surface stress of solidified billet shell in the crystallizer,as well as to digitally identify central defects in the casting billet.Among them,the recognition effect of the Unet model on central defects can reach over 90％,and the use of binarization can effectively evaluate the level of central looseness.It can be predicted that the digital system of electromagnetic metallurgy is of great significance for promoting the intelligent development of steel enterprises.
big dataartificial intelligenceelectromagnetic metallurgyphysical field visualizationdata miningintelligent detectiondigital system
万方数据
维普
