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 finflt dctcction 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 the fault is achieved by on-line monitoring the estimate of the squared coherency function, which is sensitive to the occurrence of nonlinear effects in the plant dynamics. The alarm threshold are determined by using off-line estimates of the confidence intervals of the SCF estimation. Results on data from the simulation model of the DAMADICS benchmark (which is developed to approximate the indlLstrial process in a sugar factory located in Lublin, Poland) arc outlined.