A review on guided-ultrasonic-wave-based structural health monitoring: From fundamental theory to machine learning techniques

Z Yang, H Yang, T Tian, D Deng, M Hu, J Ma, D Gao… - Ultrasonics, 2023 - Elsevier
The development of structural health monitoring (SHM) techniques is of great importance to
improve the structural efficiency and safety. With advantages of long propagation distances …

Machine learning based quantitative damage monitoring of composite structure

X Qing, Y Liao, Y Wang, B Chen, F Zhang… - International journal of …, 2022 - Taylor & Francis
Composite materials have been widely used in many industries due to their excellent
mechanical properties. It is difficult to analyze the integrity and durability of composite …

Automatic defect depth estimation for ultrasonic testing in carbon fiber reinforced composites using deep learning

X Cheng, G Ma, Z Wu, H Zu, X Hu - Ndt & E International, 2023 - Elsevier
Ultrasonic testing (UT) is commonly used to inspect the geometric shape of internal damage
in composite materials and the test results need to be interpreted by trained experts. In this …

Damage localization for composite structure using guided wave signals with Gramian angular field image coding and convolutional neural networks

Y Liao, X Qing, Y Wang, F Zhang - Composite Structures, 2023 - Elsevier
Accurate detection of damage in composite structures is of great significance to ensure safe
service and avoid catastrophic accidents. In this paper, a novel damage diagnosis method …

Towards a deep learning-based unified approach for structural damage detection, localisation and quantification

L Lomazzi, M Giglio, F Cadini - Engineering Applications of Artificial …, 2023 - Elsevier
Ultrasonic guided waves have been extensively employed for characterising structural
damage thanks to their sensitivity to defects. Although they are easy to excite and acquire …

Deep learning inversion with supervision: A rapid and cascaded imaging technique

J Tong, M Lin, X Wang, J Li, J Ren, L Liang, Y Liu - Ultrasonics, 2022 - Elsevier
Abstract Machine learning has been demonstrated to be extremely promising in solving
inverse problems, but deep learning algorithms require enormous training samples to obtain …

Defect detection in composites by deep learning using solitary waves

S Yoon, WJ Cantwell, CY Yeun, CS Cho… - International Journal of …, 2023 - Elsevier
This paper proposes a real-time non-destructive evaluation technique to detect defects in
laminated composites by deep learning using highly nonlinear solitary waves (HNSWs) …

Damage localization and characterization using one-dimensional convolutional neural network and a sparse network of transducers

A Sattarifar, T Nestorović - Engineering Applications of Artificial Intelligence, 2022 - Elsevier
Early damage identification and continuous system monitoring save dramatically
maintenance costs and increase the lifespan of priceless structures. Convolutional neural …

A multi-level damage classification technique of aircraft plate structures using Lamb wave-based deep transfer learning network

W Shao, H Sun, Y Wang, X Qing - Smart Materials and Structures, 2022 - iopscience.iop.org
Lamb wave-based damage detection is one of the most promising structural health
monitoring (SHM) technologies for aircraft structures. In this paper, a Lamb wave-based …

A Comprehensive review of emerging trends in aircraft structural prognostics and health management

S Khalid, J Song, MM Azad, MU Elahi, J Lee, SH Jo… - Mathematics, 2023 - mdpi.com
This review paper addresses the critical need for structural prognostics and health
management (SPHM) in aircraft maintenance, highlighting its role in identifying potential …