Few-shot fatigue damage evaluation of aircraft structure using neural augmentation and deep transfer learning-Reference-Cited by-同舟云学术

Few-shot fatigue damage evaluation of aircraft structure using neural augmentation and deep transfer learning

Published:2023-06 Issue: Volume:148 Page:107185
ISSN:1350-6307
Container-title:Engineering Failure Analysis
language:en
Short-container-title:Engineering Failure Analysis

Author:

Che Changchang,Wang Huawei,Xiong Minglan,Luo Shici

Publisher

Elsevier BV

Subject

General Engineering,General Materials Science

Reference28 articles.

1. Failure analysis of a cracked cylinder block assembly of an aircraft brake system;Hameed;Eng. Fail. Anal.,2022

2. Deep learning approaches to semantic segmentation of fatigue cracking within cyclically loaded nickel superalloy;Menasche;Comput. Mater. Sci,2021

3. Damage identification for a beam structure based on a PVDF piezoelectric film combined sensor;Zhao;Meas. Sci. Technol.,2021

4. Strength and stiffness degradation modeling and fatigue life prediction of composite materials based on a unified fatigue damage model;Gao;Eng. Fail. Anal.,2022

5. Accumulated fatigue damage assessment of side structural details in a double hull tanker based on spectral fatigue analysis approach;Yoris;Ocean Eng.,2022

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