A Self-Supervised Fault Detection for UAV Based on Unbalanced Flight Data Representation Learning and Wavelet Analysis

A Self-Supervised Fault Detection for UAV Based on Unbalanced Flight Data Representation Learning and Wavelet Analysis

This paper aims to build a Self-supervised Fault Detection Model for UAVs combined with an Auto-Encoder. With the development of data science, it is imperative to detect UAV faults and improve their safety. Many factors affect the fault of a UAV, such as the voltage of the generator, angle of attack...

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Bibliographic Details
Main Authors: Shenghan Zhou, Tianhuai Wang, Linchao Yang, Zhao He, Siting Cao
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Aerospace
Subjects:
fault detection
wavelet analysis
Auto-Encoder
edge detection operator
flight data
Online Access:https://www.mdpi.com/2226-4310/10/3/250

Internet

https://www.mdpi.com/2226-4310/10/3/250

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