Neural Network Model of Burden Layer Formation Dynamics in the Blast Furnace

摘要

A model of the thickness of burden layers in the ironmaking blast furnace is presented. Local layer thick- ness estimates are calculated on the basis of signals from stockrods that measure the burden (stock) level in the furnace. These estimates are used in developing a model for the relation between the layer thickness and variables such as stock level and movable armor settings.