Knowledge and mechanistic models for carbon potential correction

Knowledge based and mechanistic models for correcting carbon potential using an oxygen sensor (CPUOS) are considered. Although CPUOS is widely used, there usually exists a deviation between the true and measured values. Therefore it is important to establish a valid correction model. Experiments were designed and carried out to generate data for modelling and to identify the main influencing factors. Both single and multivariable knowledge models have been established using the support vector machine approach. Guided by these models, a mechanistic model based on the relevant theory of carbon potential has been built up. © 2008 IHTSE Partnership.