Fault detection by using the innovation signal: application to an exothermic reaction

Plants in the chemical and biochemical industries are becoming larger and more complex. The growing safety and environmental demands are forcing industry to look for new and more powerful techniques for the detection of process faults. In this paper, we present a method for detecting faults that can appear in some parts of a chemical plant. This method is based on statistical information generated by the extended Kalman filter (EKF) and is intended to reveal any drift from the normal behavior of the process. The work done in this paper is an application of the EKF to a nonlinear system such as stirred reactors in the presence of exothermic chemical reactions. We examine the abnormal behavior of a chemical reactor due to two different faults in its control parameters. The chosen reaction is a very exothermic oxido-reduction one; the oxidation of sodium thiosulfate by hydrogen peroxide.