Real-Time Prediction Model of Carbon Content in RH Process

In the Ruhrstahl–Heraeus (RH) vacuum degassing process, we propose a real-time prediction model for carbon content in molten steel, and show that decarburization endpoint can be accurately determined using this model. Firstly, applied novel off-gas analyzer measure oxide concentration produced reaction faster more accurately. Next, generate curves components measured by new analyzer. The curve describes profile well during operation, shows good agreement with actual content. order to predict operation real time, create an artificial neural network (ANN) data. By comparing at end of predicted values, confirmed excellent predictive performance ANN Finally, it is possible determine We expect proposed increase productivity RH process.