Hierarchical fuzzy Markov models for condition-monitoring and diagnosis of gas turbine engines

Abstract

A technique for determining the state of gas turbine engines is proposed based on hierarchical fuzzy Markov models. The use of fuzzy systems as a tool for the interpolation of the transition-probability matrix between base points is discussed. The possibility of using the Bayesian formula as a fuzzy logic tool for identification and simulation of Markov models is shown.