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    ARTICLE

    Extrapolation for Aeroengine Gas Path Faults with SVM Bases on Genetic Algorithm

    Yixiong Yu*

    Sound & Vibration, Vol.53, No.5, pp. 237-243, 2019, DOI:10.32604/sv.2019.07887

    Abstract Mining aeroengine operational data and developing fault diagnosis models for aeroengines are to avoid running aeroengines under undesired conditions. Because of the complexity of working environment and faults of aeroengines, it is unavoidable that the monitored parameters vary widely and possess larger noise levels. This paper reports the extrapolation of a diagnosis model for 20 gas path faults of a double-spool turbofan civil aeroengine. By applying support vector machine (SVM) algorithm together with genetic algorithm (GA), the fault diagnosis model is obtained from the training set that was based on the deviations of the monitored More >

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