This paper introduces empirical modeling techniques for process and equipment monitoring, fault detection and diagnostics, and prognostics. The paper first provides a brief background and an overview of the theoretical foundations and presents a new method for applying these methods to systems which only have one useful measured variable. A case study is then presented for the application of the method to an aircraft generator that includes Application of the proposed single variable monitoring system to the simulated aircraft generator data resulted in fault diagnosis accuracy of 96.3%, only one misdiagnosed case in 27, for the types and severities of faults considered. Future work in developing a prognostic model for a single-variable system will be outlined.


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    Title :

    Equipment Condition Monitoring and Prognostic Methods for Single Variable Systems


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    Aerospace Technology Conference and Exposition ; 2009



    Publication date :

    2009-11-10




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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