A frequency domain approach for fault detection

This paper considers the use of online frequency response estimates for change detection, which serves as a preliminary for fault detection and diagnosis. In general, a finite time frequency response estimator will always show some deviations from its nominal response even when a change has not occurred. The question we address is when does a fault detector decides if a change has occurred based on these estimates. The approach taken is based on statistical decision theory. When deviations from the nominal frequency response are detected, the detector decides with good statistical accuracy, whether a change has indeed occurred. The design is based on the Neymann-Pearson criterion, which allows for the specification of a constant false alarm rate. The performance of the detector and some practical considerations are discussed. Simulations are used to illustrate the performance and properties of the detector.