This work presents a method for detecting and identificating possible damages to propeller blades in multirotor vehicles, for a particular case study of a quadrotor. The detection method is based on a neural network, which takes as input the energy of several spectral bands of the inertial measurements and control variables, and outputs a measure of how damaged a propeller is. The ability of the network to correctly generalize from a limited dataset will be shown by training it using data gathered from an indoor, controlled environment, and testing it using data from outdoor flights.


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    Title :

    Neural network-based propeller damage detection for multirotors


    Contributors:


    Publication date :

    2023-06-06


    Size :

    4613757 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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