Development of the Sensory Network for the Vibration-based Fault Detection and Isolation in the Multirotor UAV Propulsion System
[ 1 ] Instytut Automatyki, Robotyki i Inżynierii Informatycznej, Wydział Elektryczny, Politechnika Poznańska | [ P ] pracownik
2018
rozdział w monografii naukowej / referat
angielski
- Multirotor UAV
- Fault Detection
- Propeller Damage
- Vibration Analysis
- Random Decision Trees
EN In this paper, a fault detection and isolation (FDI) system for propeller impairments of the multirotor UAV is presented. The algorithm is based on the processing of signal vectors from the set of vibration sensors located close to the propulsion units. Axial and radial vibrations are measured using MEMS accelerometers that provide data for the feature extraction based on the Fast Fourier Transform (FFT). Characteristic fault signatures extracted from vibration signals are used to detect and localize damaged blades using the set of random decision trees. A method was evaluated with data gathered during numerous test flights and validated in relation to signal acquisition time and number of classifiers in the ensemble. Results show over 95% sensitivity in detecting and isolating faulty rotor states. The presented approach is an effective and low-cost solution, very versatile to implement in the arbitrary UAV.
102 - 109
CC BY-NC-ND (uznanie autorstwa - użycie niekomercyjne - bez utworów zależnych)
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