TOWARDS A BETTER INTEGRATION OF PASSIVE ROBUST INTERVAL-BASED FDI ALGORITHMS

Abstract

This work proposes a new interval model-based fault diagnosis method that improves the integration of the fault detection and isolation tasks. A new interface between fault detection and fault isolation is presented that takes into account several sources of information about the fault signal activation. In particular, a combination of four fault signature matrices is used for the fault isolation process. The matrices store knowledge about the faulty system behaviour: Boolean fault signal occurrence, signs of residual violation, sensitivities and fault signal occurrence order. Finally, the proposed method is applied to detect and isolate faults of the Barcelona's urban sewer system limnimeters.