XGBoost-based Evaluation of the Dosing State of the Converter Valve Cooling System

The converter valve cooling system is an important part to ensure the stable operation of the converter station. Circulating water is prone to breeding bacteria and algae and scaling, which seriously affecting the heat exchange efficiency of the converter valve cooling system. In this paper, a method for evaluating the automatic dosing state of the ultra-high pressure converter valve cooling system based on XGBoost is proposed. First, for the main components of the converter valve cooling system, 10 characteristic indicators such as inlet valve pressure, inlet valve temperature, spray water conductivity, and valve hall temperature are extracted. Then the preprocessed data is imported into the XGBoost classifier for training, realizing the parameter optimization through grid search. Finally, the field data of a converter station in Jiangsu Province is utilized to verify the effect of the model. The results show that the model’s evaluation accuracy rate reaches 92%.