A method for detection and diagnosis on batch fermentations

In this work we present some basic ideas about detection and diagnosis of faults and abrupt dynamic changes in batch fermentations. Our work focuses on the simultaneous use of two detection methods (residual based and balances based) within the estimation procedure. The idea behind the use of both methods is that the weakness of one of them can be compensated by the use of the other one. Thus the simultaneous use of both methods allows detecting and possibly isolating a wide range of faults. Observations such as the effect of nonlinearities on the detection tests and robustness to model uncertainty are discussed. Numerical results on a particular case, the xanthan gum batch fermentation, are presented. Simulated faults and abnormal behaviors were promptly detected but diagnostics showed mixed results.