Fault Diagnosis of Dynamical Systems Based on State-Set Observers

Abstract

This paper shows how state-set observation can be used to detect and identify faults in a dynamical systems with bounded measurement uncertainties. A state-set observer uses the process model and the measured input and output sequence to determine the set of states the process can be in. For diagnosis, a bank of observers is used based on the process models for every fault case. IT an observer arrives at an empty set of states, the measured behaviour is inconsistent with the model of the corresponding fault and this fault is known to be not present. The remaining faults form the set of fault candidates. To further distinguish these, fault probabilities are calculated. A method for determining conditional probabilities from the observation sets is developed. This allows to combine the diagnostic strength of state-set observation and stochastic observation