The paper describes a new strategy for real-time sensor diagnostics that is based on the statistical correlation of various sensor signal pairs. During normal fault-free operation there is a certain correlation between the sensor signals which is lost in the event of a fault. The proposed algorithm quantifies the correlation between sensor signal pairs using real-time scalar metrics based on the Mahalanobis-distance concept. During normal operation all metrics follow a similar pattern, however in the event of a fault; metrics involving the faulty sensor would increase in proportion to the magnitude of the fault. Thus, by monitoring this pattern and using a suitable fault-signature table it is possible to isolate the faulty sensor in real-time. Preliminary simulation results suggest that the strategy can mitigate the false-alarms experienced by most model-based diagnostic algorithms due to an intrinsic ability to distinguish nonlinear vehicle behavior from actual sensor faults.


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    Titel :

    Diagnostics based on the Statistical Correlation of Sensors


    Weitere Titelangaben:

    Sae International Journal of Passenger Cars- Electronic and Electrical Systems
    Sae Int. J. Passeng. Cars – Electron. Electr. Syst


    Beteiligte:

    Kongress:

    SAE World Congress & Exhibition ; 2008



    Erscheinungsdatum :

    2008-04-14


    Format / Umfang :

    9 pages




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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