Turbofan Performance Deterioration Tracking Using Nonlinear Models and Optimization Techniques

Abstract

A method of identifying the gradual deterioration in the components of jet engines is presented. It is based on the use of an engine model which has the capability to adapt component condition parameters, so that measured quantities are matched. The main feature of the method is that it gives the possibility to identify performance deviations in a number of parameters larger than the number of measured quantities. This is achieved by optimizing a cost function which incorporates not only measurement matching terms, but also terms expressing various constraints resulting from the physical knowledge of the deterioration process. Time series of data representing deterioration scenarios are used to demonstrate the method’s capabilities. The test case considered is a twin spool partially mixed turbofan, representative of present-day large civil aeroengines. Implementation aspects, related to both the measurement set and the identification algorithms are discussed. An interpretation of the output of the method in function of different parameters entering the diagnostic problem is presented.