Fault in the propulsion system of UAVs is one of the main causes for incidents and loss of the aircraft. In electric propulsion systems typical faults are ball-bearing degradation leading to increased friction and losses, as well as propeller icing when operating in cold conditions. In this paper we propose a fault detection and isolation (FDI) framework that uses model-based estimators of the various faults, implemented with multiple Kalman and Bayes filters. The method is tested and shown to be effective in a simulation setup using a fixed-wing UAV simulator.


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    Title :

    Detection and Isolation of Propeller Icing and Electric Propulsion System Faults in Fixed-Wing UAVs


    Contributors:
    Haaland, O. M. (author) / Wenz, A. W. (author) / Gryte, K. (author) / Hann, R. (author) / Johansen, T. A. (author)


    Publication date :

    2021-06-15


    Size :

    1780170 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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