Diagnosis and Prognosis of Faults in High-Speed Aeronautical Bearings with a Collaborative Selection Incremental Deep Transfer Learning Approach

Diagnosis and Prognosis of Faults in High-Speed Aeronautical Bearings with a Collaborative Selection Incremental Deep Transfer Learning Approach

The diagnosis and prognosis of aeronautical-bearing health conditions are essential to proactively ensuring efficient power transmission, safety, and reduced downtime. The rarity of failures in such safety-critical systems drives this process towards data-driven analytics of fault injection and agin...

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Bibliographic Details
Main Authors: Tarek Berghout, Mohamed Benbouzid
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Applied Sciences
Subjects:
aircraft bearing
aircraft engine
deep learning
fault diagnosis
health stage
long short-term memory
Online Access:https://www.mdpi.com/2076-3417/13/19/10916

Internet

https://www.mdpi.com/2076-3417/13/19/10916

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