Hybrid Fault Diagnosis: Application to a Gas Turbine Engine

Abstract

This paper presents a hybrid framework for fault diagnosis of complex systems that are modeled by hybrid automata. A bank of residual generators is constructed based on the continuous models of the system. Each residual generator is modeled by a discrete-event system (DES). Next, the DES models of the residual generators and the DES model of the hybrid plant are combined to build an “extended DES” model. A hybrid diagnoser is constructed based on the extended DES model. The hybrid diagnoser effectively combines the readings of discrete sensors and the information supplied by the residual generators (which is based on continuous sensors) to determine the health status of the hybrid plant. The hybrid diagnosis approach is employed to investigate faults in the fuel supply system and the nozzle actuator of a single-spool turbojet engine with an afterburner.