A failure diagnosis system based on a neural network classifier for the Space Shuttle Main Engine

Abstract

A conceptual design of a model based failure deeteection and diagnosis system is deeveloped for the Space Shuttle Main Engine. This design relies on the accurate and reliable identification of the parameters of the highly nonlinear and very complex engine. The design approach is presented in some detail and results for a failed valve are presented. These preliminary results verify that the developed parameter identification technique, together with a neural network classifier, can be used for this purpose.