A gas path diagnostic and prognostic approach for gas turbine applications

Gas turbine engines experience degradation over time that cause great concern to gas turbine users on engine reliability, availability and operating costs. It has been realized in recent years that gas turbine diagnostics and prognostics is one of the key technologies to enable the move from time-scheduled maintenance to condition-based maintenance in order to improve engine reliability and availability and reduce life cycle costs. The objective of this paper is to introduce a systematic diagnostic and prognostic approach to assess the health condition and estimate the remaining useful life of gas turbine engines before their next major overhaul. A non-linear Gas Path Analysis (GPA) approach is used to assess engine performance degradation with the confidence measured by a GPA Index. A combined regression techniques, including both linear and quadratic models, is proposed to predict the remaining useful life of gas turbine engines. A statistic "Compatibility Check" is used to determine the switch point from linear regression to quadratic regression. The developed diagnostic and prognostic approach has been applied to a model gas turbine engine similar to Rolls-Royce Industrial AVON 1535 implemented with compressor degradation over time. The analysis shows that the developed diagnostic and prognostic approach has great potential to provide an estimation of engine remaining useful life before next major overhaul for gas turbine engines experiencing a typical slow degradation.