数据驱动的铜锍吹炼造渣过程混合动态模型

For the slag-making stage of the matte converting process with strong dynamic characteristics, a data-driven hybrid dynamic model was proposed which includes a nonlinear reaction kinetic model based on metallurgical reaction kinetics and an optimization model for correction factor of its kinetic coefficient based on production data. Taking into account the large amount of calculation for the optimization model, a typical set with small-scale and representative sample was constructed and a hybrid intelligent algorithm was proposed, which ensure that the optimal correction factor can be obtained effectively during searching process and the dynamic changes of the slag-making process can be truly reflected by the amended kinetic model. Contrasting with the real value of PS converter in a smeltery, the maximum relative error of the simulation result of the dynamic model proposed is less than 5%, which show that the model effectively describes the dynamic process of the components and the temperature of matte with time changes in the slag-making process.