We propose a new method for local linear smoothing, filtering and prediction of noisy data. Its novelty consists in two of its steps: a sliding window filter that uses Student’s t-statistics to perform smoothing and filtering, and a trend change detection scheme that uses a convex hull construction to determine a change of slope or intercept of the local linear trend. The final linear trend detected is used for linear prediction and interval estimation. The application of the scheme to gas-turbine engine prognostics is presented.


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    Title :

    Aeroengine Prognostics via Local Linear Smoothing, Filtering and Prediction


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    Power Systems Conference ; 2004



    Publication date :

    2004-11-02




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English






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