Gas turbine engine condition monitoring using statistical and neural network methods

This paper focuses on the two general approaches being investigated for condition monitoring systems: static pattern analysis approach and the dynamical systems approach. In each, statistical and neural network methods are used. The dynamical systems approach lends itself to model-based condition monitoring systems. The performances of the different methods for the monitoring of the complex aircraft gas turbine engine is described, based on real engine data