Study On Optimizing Models For Sintering Proportioning,BF Ironmaking And Scheduling

The procedure in blast furnace ironmaking includes many complicated sub process. It is hard to explain some phenomena clearly. Prediction and optimization for operation of the section can maintain stable process, improve quality and quantity of products and reduce the cost of products.Presently, there are some limits in the known forecasting and optimal model for ironmaking. Most model only emphasis on optimization of processing operation, there are no mature scheduling models reported or used in this section.Aiming at sinter proportioning, burden distribution of blast furnace, judge and prediction of operational state of BF and scheduling in"Sinter-BF"section, forecasting and optimal models are built.â‘ In the optimized model for sinter proportioning:1) GA (Genetic Algorithm) is used in optimizing sinter proportioning. The model can guarantee the chemical and physical demand of sinter and reduce the cost of sinter.2) Multiple stepwise regression is used to build the relation between physical property of sinter and sinter proportioning. It is helpful to optimize sinter proportioning.â‘¡In the model for burden distribution of blast furnace:1) Combined Newton law of motion with angle correction, prediction of O/C, a simulation model for burden distribution of BF is built. In the model, two trajectory lines are used as burden flow trajectory, which is accord with reality. The burden profile is used linearization treatment.2) Aiming at minimal difference of O/C between model and object, model can optimize operational parameter accord to object O/C with GA.3) An experimental setup that proportion of size is 1:15 is used to verity the burden trajectory and effect of operational parameters to different size burden.4) Image processing method is used to study change law of dumping angel with experiment.â‘¢In the model for intelligent forecasting and judge operational state of BF:1) An intelligent judging model for operational state of BF is built with GA and fuzzy cluster. The model can be built in data mining automatically.2) An intelligent forecasting model for permeability index is built with wavelet analysis and support vector machine. Compared with other intelligent techniques, the model has higher forecasting accuracy and generalized ability.â‘£In the scheduling model:1) The model integrated Petri Net and GA (genetic algorithm) as suitable tools for simulation and optimization of scheduling to sintering and BF process.2) By analysis, the conclusion is drawn that scheduling with optimized values can maintain continuity of key operations , can satisfy order of hot metal in maximal degree and can keep the best stability of key storages.3) The model can easily fulfill logistics traceability with reversing model.4) The model can fulfill optimization scheduling in maintenance plan.