Burden Surface Shape Modeling and Charging Matrix Optimization for the Blast Furnace Charging Process

Charging operation is an essential regulatory measure at the top of blast furnaces. Accurately predicting the burden surface shape (BSS) and reasonably adjusting the charging matrix (CM) are vital for achieving precise charging operation. However, the existing methods neglect the influence of the burden motion state, which greatly limits prediction accuracy of BSS, and complex constraints of CM further cause the lack of effective CM optimization strategies. To address these challenges, a BSS prediction model and a CM optimization strategy are innovatively proposed in this article. First, the burden motion state under different accumulation behaviors is introduced into the BSS modeling, and the iterative solution of BSS is realized with the volume conservation constraint. Then, a hybrid constraint-handling mechanism consisting of the infeasible solution rejection method and the penalty function method is proposed, which is used to develop a CM optimization model. Finally, an improved algorithm, named dynamic heterogeneous multiswarm particle swarm optimization, is designed to solve the optimal CM (i.e., the best particle in the population). The prediction results of BSS model are highly similar to those of the model based on discrete element method, and the effectiveness of CM optimization strategy is validated in two simulation cases.