Using Multiple Deep Neural Networks Platform to Detect Different Types of Potential Faults in Unmanned Aerial Vehicles

Using Multiple Deep Neural Networks Platform to Detect Different Types of Potential Faults in Unmanned Aerial Vehicles

Many researchers developed new algorithms to predict the faults of unmanned aerial vehicles (UAV). These algorithms detect anomalies in the streamed data of the UAV and label them as potential faults. Most of these algorithms consider neither the complex relationships among the UAV variables nor the...

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Bibliographic Details
Main Authors: Ahmad Alos, Zouhair Dahrouj
Format: Article
Language:English
Published: Departamento de Ciência e Tecnologia Aeroespacial 2021-02-01
Series:Journal of Aerospace Technology and Management
Subjects:
uav
deep neural network
anomaly detection
abnormal
fault
Online Access:https://www.scielo.br/pdf/jatm/v13/2175-9146-jatm-13-e1321.pdf

Internet

https://www.scielo.br/pdf/jatm/v13/2175-9146-jatm-13-e1321.pdf

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