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• W2112723218 abstract "Gas turbine engines experience degradations over time that cause great concern to gas turbine users on engine reliability, availability and operating costs. 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. This paper describes a prognostic approach to estimate the remaining useful life of gas turbine engines before their next major overhaul based on historical health information. 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 transition point from a linear regression to a quadratic regression. The developed prognostic approach has been applied to a model gas turbine engine similar to Rolls-Royce industrial gas turbine AVON 1535 implemented with compressor degradation over time. The analysis shows that the developed prognostic approach has a great potential to provide an estimation of engine remaining useful life before next major overhaul for gas turbine engines experiencing a typical soft degradation." @default.
• W2112723218 created "2016-06-24" @default.
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• W2112723218 date "2009-10-01" @default.
• W2112723218 modified "2023-10-14" @default.
• W2112723218 title "Gas turbine performance prognostic for condition-based maintenance" @default.
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• W2112723218 doi "https://doi.org/10.1016/j.apenergy.2009.02.011" @default.
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