Actuator fault detection and isolation system for multirotor unmanned aerial vehicles
[ 1 ] Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ 2 ] Instytut Robotyki i Inteligencji Maszynowej, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ SzD ] doktorant ze Szkoły Doktorskiej | [ P ] pracownik
2022
rozdział w monografii naukowej / referat
angielski
- UAV
- fault detection
- fault classification
- ANN
- IMU
- FDI
EN This article presents a new actuator fault detection and isolation method for multirotor unmanned aerials (UAVs). The UAV community raises the need to develop a highly efficient classifier capable of early detection of failures and fully independent of other systems. This paper presents the entire process of preparing the method discussed and its implementation in the embedded system. The measurements of four accelerometers were digitally processed data, the main element of which was the frequency domain analysis. The feature vectors prepared in this way were used to train the artificial neural network. The network model has been implemented on a microcontroller. The tests were carried out using data collected during actual flight in various configurations of damaged propellers. The overall accuracy of the proposed method was 98.08% without the presence of false alarms. The total processing time was also tested, demonstrating real-time classification capability onboard the autonomous flying robot. The efficiency results were compared with the random forest method.
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