Data-Driven Modelling and Production Intelligence Upgrading in Blast Furnace Ironmaking
In the current industrial development,blast furnace ironmaking,as one of the most complex industrial activities,should actively use data-driven modelling to make a good prediction of iron silica content,so as to improve the quality of production with scientific indicators.However,the current application of data-driven modelling is poor,while the ironmaking platform lacks digital optimisation.For this reason,after proposing a local perception-enhanced feature,time-attention model,data-driven modelling is first optimized with good prediction of iron silica content.Secondly,the analysis of the industrial internet platform architecture is carried out,with the help of intelligent upgrading of the industrial platform,the ironmaking process can be guaranteed to be more efficient and smooth,in the expectation that the development of the steel plant can be promoted.
NETL
NSTL
万方数据
