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Communication Dans Un Congrès Année : 2022

Deep-Learning fault detection and classification on a UAV propulsion system

Pierre-Yves Brulin
  • Fonction : Auteur
Fouad Khenfri
Nassim Rizoug

Résumé

A fault detection and identification method using a Deep-Learning classification method is used to identify several faults that may occur on a UAV propulsion system. Training is performed from a dataset acquired from a simplified multiphysics simulation of the system which allows for the generation of large datasets of modular, interconnected and scalable components of various sizes and performances. We aim to provide a model able to identify faults occurring on a propulsion system using a reduced set of input signals.
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Dates et versions

hal-04404806 , version 1 (19-01-2024)

Identifiants

  • HAL Id : hal-04404806 , version 1

Citer

Pierre-Yves Brulin, Fouad Khenfri, Nassim Rizoug. Deep-Learning fault detection and classification on a UAV propulsion system. 2022 24th European Conference on Power Electronics and Applications (EPE'22 ECCE Europe), Sep 2022, Hannover, Germany. ⟨hal-04404806⟩
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