Fault Diagnosis using a Timed Discrete Event Approach based on Interval Observers

Abstract

This paper proposes a fault diagnosis method using a timed discrete-event approach based on interval observers which improves the integration of fault detection and isolation tasks. The interface between fault detection and fault isolation considers the degree of fault signal activation and the occurrence time of the diagnostic signals using a combination of several theoretical fault signature matrices which store the knowledge of the relationship between diagnostic signals and faults. As a novelty, this paper proposes to implement the fault isolation module using a timed discrete event approach in spite of using an analytical fault detection model. In this way, the diagnosis result will be enhanced since the occurrence of a fault generates a unique sequence of observable events (fault signals) that will be recognized by the isolation module implemented as a timed discrete event system. The states and transitions that characterize such a system can be inferred directly from the relation between fault signals and faults. The proposed fault diagnosis approach is applied to detect and isolate faults of the Barcelona's urban sewer system limnimeters (level meter sensors).