Model-Free Fault Detection: a Spectral Estimation Approach Based on Coherency Functions

Previdi F., T. Parisini

This paper presents a model±free fault detection technique based on the use of a speci®c spectral analysis tool, namely,
squared coherency functions. The fault±free dynamic behaviour of the plant considered is described by a stochastic linear
state equation, where the stochastic part is due to unpredictable external disturbances. A fault is assumed to be a nonlinear dynamic perturbation of the linear plant dynamics. The detection ofthe fault is achieved by on±line monitoring the estimates of a squared coherency function that is sensitive to the occurrences of non-linear events aŒecting the plant
dynamics. A theoretical analysis of the fault-detectability issue is made and an original algorithm for a low±bias
estimation of the squared coherency function is exploited to minimize the false-alarm rate. Finally, experimental results
obtained by using real data concerning the three-tank benchmark problem are reported, showing the eŒectiveness of the
proposed methodology.

Download 2001 Int Jour Control – Fault Detection