Residuals are typically used as indicators of normal (non-faulty) vs. abnormal (faulty) behavior in dynamic systems. The nonfaulty residuals are assumed to be Gaussian, zero-mean, uncorrelated, with a known variance. However, in many practical situations, the assumption of Gaussian-ness may not be valid. We propose a new type of fault detector which is essentially independent of the distribution of the residuals. This fault detector is based on an autoregressive modeling of the residual signal, augmented by a sample variance calculation. Usefulness of this new detector is demonstrated with the experimental fault data obtained at NASA Langley Research Center.


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    Titel :

    Fault detection: the effect of unknown distribution of residuals


    Beteiligte:
    Chowdhury, F. (Autor:in) / Belcastro, C.M. (Autor:in) / Jiang, B. (Autor:in)


    Erscheinungsdatum :

    2004-01-01


    Format / Umfang :

    427058 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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