Endpoint carbon content prediction of VOD using RBF neural network

VOD(Vacuum Oxygen Decarburization) is a special furnace steel refining process. In the process, the endpoint carbon content prediction is a very important criteria for smelting products. The mathematical modeling of VOD often does not reflect the actual situation adequately. Using RBF neural network, the model of the VOD process is established to predict endpoint carbon content. Main factors affecting the endpoint carbon content are chosen as the input of the RBF network. The simulation results show the prediction data can be used in the VOD process to is predict the endpoint carbon content.