组织性能预测技术及其在智能热轧中的核心作用

The predicting technologies for microstructure and properties and their core roles in smart hot rolling processes

在利用工业大数据指导钢铁企业进行智能热轧的生产实践中,发现钢铁工业数据在建模中存在诸多问题,如数据信噪比低、分布不均衡等,这给基于数据驱动的智能热轧工艺优化设计技术的实现造成了严重阻碍。围绕热轧生产中带钢奥氏体再结晶、奥氏体相变、微合金碳氮化物析出和组织性能对应关系以及氧化铁皮演变过程,结合人工智能理论对组织性能预测技术在智能热轧中发挥的核心作用进行了阐述,并对东北大学2011钢铁共性技术协同创新中心先进短流程工艺技术与装备方向在钢铁智能制造方面研究中取得的成果进行了介绍。

It is found that there are many problems in the modeling of industrial data of hot rolled strips in application of industrial big data in intelligent hot rolling of iron and steel enterprises,such as low signal-to-noise ratio and unbalanced distribution of data,which seriously hinders the realization of data-driven intelligent hot rolling process optimization design technology.Based on the process of austenite recrystallization,austenite transformation,precipitation of microalloyed carbide and nitride,the relationship of microstructure and property and the evolution of oxide scale in hot rolling production,the core role of the prediction technology of microstructure and property in intelligent hot rolling with the theory of artificial intelligence was described.Besides,the achievements in the research of intelligent manufacturing of iron and steel of Advanced Short Process Technology and Equipment Direction of the 2011 General Technology Co-innovation Center for Iron and Steel of Northeast University were introduced.