Modeling switched behavior to monitor energy-based dynamical systems

Nowadays, a wide number of manufacturing systems are usually coupled discrete and continuous dynamic behaviors. This paper deals with the design of a novel framework related to the fault diagnosis issue merging quantitative and qualitative reasoning so as to accurately monitor several fault kinds affecting such hybrid systems. Two different structural fault diagnosis approaches are compared. Firstly, the Hybrid Bond Graph (HBG) representation (quantitative way) is used to obtain the Global Analytical Redundancy Relations (GARRs) dedicated to Fault Detection and Isolation (FDI) tasks. Secondly, the qualitative approach utilizes the possible conflicts which are deduced from the Directed Behavioral Hypergraph (DBH) description and able to study the temporal and qualitative impacts related to sensor and actuator faults. Afterwards qualitative and quantitative methods are compared and discussed so as to analysis the ability to diagnose the dynamical hybrid systems.