LEARNING METHOD OF LEVEL LOWERING SPEED PREDICTION MODEL FOR BLAST FURNACE, LEVEL LOWERING SPEED PREDICTION MODEL FOR BLAST FURNACE, PREDICTION METHOD OF LEVEL LOWERING SPEED FOR BLAST FURNACE, BLAST FURNACE OPERATION GUIDANCE METHOD, CONTROL METHOD OF LEVEL LOWERING SPEED FOR BLAST FURNACE, MOLTEN IRON PRODUCTION METHOD, BLAST FURNACE OPERATION METHOD, AND A LEARNING DEVICE FOR LEVEL LOWERING SPEED PREDICTION MODEL FOR BLAST FURNACE

摘要

PROBLEM TO BE SOLVED: To provide a learning method of a level lowering speed prediction model for a blast furnace, level lowering speed prediction model for a blast furnace, prediction method of level lowering speed for a blast furnace, blast furnace operation guidance method, control method of level lowering speed for a blast furnace, molten iron production method, blast furnace operation method, and a learning device for a level lowering speed prediction model for a blast furnace, by which a level lowering speed in a blast furnace can be accurately predicted.;SOLUTION: The learning method of a level lowering speed prediction model for a blast furnace according to the present invention includes at least one operation variables consisting of a flow rate in blast furnace operation, enrichment oxygen flow, pulverized coal blowing amount; ventilation moisture content; and a coke ratio at the top of the furnace, as an input variable. The learning method includes: a step of constructing a model of a level lowering speed prediction model for a blast furnace which uses a level lowering speed of a blast furnace at the time step one time step ahead of the current time as an output variable as a recursive neural network model; and a step of determining a learning parameter of a level lowering speed prediction model of a blast furnace using learning data based on the raw material residence time in the blast furnace.;SELECTED DRAWING: Figure 1;COPYRIGHT: (C)2020,JPO&INPIT