Recent Advancements in Guided Ultrasonic Waves for Structural Health Monitoring of Composite Structuresopen access
- Authors
- Tanveer, Mohad; Elahi, Muhammad Umar; Jung, Jaehyun; Azad, Muhammad Muzammil; Khalid, Salman; Kim, Heung Soo
- Issue Date
- Dec-2024
- Publisher
- MDPI
- Keywords
- structural health monitoring; ultrasonic techniques; laminated composite structures; non-destructive testing; machine learning
- Citation
- Applied Sciences, v.14, no.23, pp 1 - 22
- Pages
- 22
- Indexed
- SCIE
SCOPUS
- Journal Title
- Applied Sciences
- Volume
- 14
- Number
- 23
- Start Page
- 1
- End Page
- 22
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/56454
- DOI
- 10.3390/app142311091
- ISSN
- 2076-3417
2076-3417
- Abstract
- Structural health monitoring (SHM) is essential for ensuring the safety and longevity of laminated composite structures. Their favorable strength-to-weight ratio renders them ideal for the automotive, marine, and aerospace industries. Among various non-destructive testing (NDT) methods, ultrasonic techniques have emerged as robust tools for detecting and characterizing internal flaws in composites, including delaminations, matrix cracks, and fiber breakages. This review concentrates on recent developments in ultrasonic NDT techniques for the SHM of laminated composite structures, with a special focus on guided wave methods. We delve into the fundamental principles of ultrasonic testing in composites and review cutting-edge techniques such as phased array ultrasonics, laser ultrasonics, and nonlinear ultrasonic methods. The review also discusses emerging trends in data analysis, particularly the integration of machine learning and artificial intelligence for enhanced defect detection and characterization through guided waves. This review outlines the current and anticipated trends in ultrasonic NDT for SHM in composites, aiming to aid researchers and practitioners in developing more effective monitoring strategies for laminated composite structures.
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- Appears in
Collections - College of Engineering > Department of Mechanical, Robotics and Energy Engineering > 1. Journal Articles

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