Few-shot structural repair decision of civil aircraft based on deep meta-learning

C Che, H Wang, X Ni, M Xiong - Engineering Applications of Artificial …, 2023 - Elsevier
To solve the difficulties in extracting general features of few-shot high-dimensional structural
health monitoring data and making accurate repair decision, a civil aircraft structural repair …

A Bayesian fusion method for composite damage identification using Lamb wave

H Huo, J He, X Guan - Structural Health Monitoring, 2021 - journals.sagepub.com
This study presents a novel method for composite damage identification using Lamb wave.
A probabilistic integration of the elliptical loci method and the RAPID (reconstruction …

In-situ fatigue life prognosis for composite laminates based on stiffness degradation

T Peng, Y Liu, A Saxena, K Goebel - Composite Structures, 2015 - Elsevier
In this paper, a real-time composite fatigue life prognosis framework is proposed. The
proposed methodology combines Bayesian inference, piezoelectric sensor measurements …

A probabilistic crack size quantification method using in-situ Lamb wave test and Bayesian updating

J Yang, J He, X Guan, D Wang, H Chen… - … Systems and Signal …, 2016 - Elsevier
This paper presents a new crack size quantification method based on in-situ Lamb wave
testing and Bayesian method. The proposed method uses coupon test to develop a baseline …

Graphene enhanced flexible piezoelectric transducers for dynamic strain measurement: from material preparation to application

J He, Z Fang, C Gao, W Zhang… - Smart Materials and …, 2023 - iopscience.iop.org
In this study, graphene particles are introduced to the lead magnesium niobate-lead titanate
and polyvinylidene fluoride (PVDF) to form a flexible ternary composite. The graphene …

Multi-fidelity data aggregation using convolutional neural networks

J Chen, Y Gao, Y Liu - Computer methods in applied mechanics and …, 2022 - Elsevier
Multi-fidelity data exist in almost every engineering and science discipline, which can be
from simulation, experiments, and a hybrid form. High fidelity data are usually associated …

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

C Che, H Wang, M Xiong, S Luo - Engineering Failure Analysis, 2023 - Elsevier
To solve the problems of few-shot samples, different structural degradation trends and poor
damage evaluation effect in fatigue damage evaluation of aircraft structure, an intelligent …

Model-driven fatigue crack characterization and growth prediction: A two-step, 3-D fatigue damage modeling framework for structural health monitoring

L Xu, K Wang, X Yang, Y Su, J Yang, Y Liao… - International Journal of …, 2021 - Elsevier
Prevailing fatigue damage evaluation approaches that make use of the acoustic nonlinearity
of guided ultrasonic waves (GUWs) are sustained by simplified models, most of which depict …

Uncertainty quantification of fatigue SN curves with sparse data using hierarchical Bayesian data augmentation

J Chen, S Liu, W Zhang, Y Liu - International Journal of Fatigue, 2020 - Elsevier
A novel statistical uncertainty quantification (UQ) method for fatigue SN curves with sparse
data is proposed in this paper. Sparse data observation is very common in fatigue testing …

Monitoring fatigue cracks in riveted plates using a sideband intensity based nonlinear ultrasonic technique

B Hu, U Amjad, T Kundu - Ultrasonics, 2024 - Elsevier
Aluminum structures are routinely used in aircraft due to their lightweight and corrosion
resistance properties. Multi-layered aluminum plates are generally joined by rivets forming …