AN EFFICIENT FORMULATION FOR BATCH REACTOR DATA RECONCILIATION

An efficient formulation of the data reconciliation problem applied to batch reactor experiments is proposed and discussed in comparison wit h other works reported on this subject in the Literature. Under the as sumption that all components in the reaction are known experimentally and that their chemical compositions are defined, atomic balances are used as constraints in order to correct raw data values. The formulati on is based on an a posteriori simultaneous treatment of all measureme nts over the whole time of experimentation. The main point of interest in this formulation is the preservation of the measurement identity i n each sample. Even if component holdups are systematically involved i n mass balances by pairs to estimate a difference in time, here we cor rect each component measurement and each sample independently. On this basis, it is shown how classical statistical tests can be used to dis criminate gross errors. A case study built from simulated true and noi sy data gives an overview of the performances of the method. The resul ts state that the overall time formulation is more powerful than the c lassical one, which is essentially based on a sequential treatment by periods of time. Evaluation of the performance for three adapted stati stical tests leads us to conclude that the generalized likelihood rati o (GLR) is not only the most appropriate but also the most efficient t est.