Hybrid Model for Predicting Oxygen Consumption in BOF Steelmaking Process Based on Cluster Analysis

Abstract

The amount of oxygen blown into the converter directly affects the productivity of the converter and the quality of the molten steel, so it is crucial to accurately predict oxygen consumption. Herein, a hybrid model for predicting oxygen consumption in basic oxygen furnace steelmaking process is established. The oxygen consumption of converter is divided into two types: the determined oxygen consumption and the estimated oxygen consumption. The determined oxygen consumption is calculated by mechanism model. And the estimated oxygen consumption is calculated by statistical model. The method of cluster analysis is also introduced into the model. After clustering the data, a statistical model for predicting the estimated oxygen consumption in each subcategory is established, which further improves the prediction accuracy of the model. After dividing the original data into three categories, the hit rate of the hybrid model is 93.3%, when the relative errors of the model are restricted within 5%. As a result, the hybrid model is fully capable of predicting oxygen consumption in converters.