The AUVs (Autonomous Underwater Vehicle) are complex technical systems which safety and reliable operation deserves particular attention. Navigation-piloting sensors are important components of the AUVs which are necessary to control a motion trajectory. Since malfunctions and faults occurring in these sensors can lead to erroneous mission fulfillment or loss of the vehicle, it is necessary to detect and isolate a faulty sensor early. There are some different methods of fault diagnosis: signal-based, analytical model-based, knowledge-based. To diagnosis the AUV navigation-piloting sensors, analytical model-based method is applied. The mathematical model which describes the normal AUV dynamic behavior is used. The diagnosis process based on checking analytical relationships between input and output signals of the AUV is performed. In order to estimate the sensors output signals, observer-based method is used. In this case, the actual AUV sensor measurement is compared with a fault-free observer output signal driven by the control signals and sensors measured variables. Difference between the actual sensor measurement and corresponding observer output signal is a residual signal which carries the information about the faults in the sensors. The residuals values are evaluated for diagnosis purposes. There are several methods of the residual evaluation: threshold logic, statistical decision theory, pattern recognition, fuzzy decision-making, neural networks. The faults in navigation-piloting sensors are incipient mainly. From this kind of fault diagnosis point of view, application of fuzzy logic is of high practical interest. The task of diagnosing of the AUV navigation-piloting sensors based on fuzzy logic is considered. Fuzzy logic is applied for residual evaluation as well as for diagnostic decision-making.


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    Title :

    Sensor fault diagnosis in autonomous underwater vehicle


    Additional title:

    Sensorfehlerdiagnose in Unterwasserfahrzeugen


    Contributors:


    Publication date :

    2003


    Size :

    6 Seiten, 3 Bilder, 5 Quellen



    Type of media :

    Conference paper


    Type of material :

    Storage medium


    Language :

    English




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