Model-free actuator fault detection using a spectral estimation approach: the case of the DAMADICS benchmark problem

This paper presents the application to the DAMADICS benchmark fault detection problem of a model-free fault detection technique based on the use of a specific spectral analysis tool, namely, the Squared Coherency Functions (SCFs). The detection of a fault is achieved by on-line monitoring the estimate of the squared coherency function, which is sensitive to the occurrence of significative changes in the plant dynamics. The alarm threshold are based on the estimates of the confidence intervals of the SCF. Results on both simulation and real data of the DAMADICS benchmark (which is developed to approximate the industrial process in a sugar factory located in Lublin, Poland) are outlined.

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