Recent Advancements in Guided Ultrasonic Waves for Structural Health Monitoring of Composite Structures
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 t...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/14/23/11091 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846124450583412736 |
|---|---|
| author | Mohad Tanveer Muhammad Umar Elahi Jaehyun Jung Muhammad Muzammil Azad Salman Khalid Heung Soo Kim |
| author_facet | Mohad Tanveer Muhammad Umar Elahi Jaehyun Jung Muhammad Muzammil Azad Salman Khalid Heung Soo Kim |
| author_sort | Mohad Tanveer |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9c1cf2e0a2a94fa599b7da98ef636613 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-9c1cf2e0a2a94fa599b7da98ef6366132024-12-13T16:22:47ZengMDPI AGApplied Sciences2076-34172024-11-0114231109110.3390/app142311091Recent Advancements in Guided Ultrasonic Waves for Structural Health Monitoring of Composite StructuresMohad Tanveer0Muhammad Umar Elahi1Jaehyun Jung2Muhammad Muzammil Azad3Salman Khalid4Heung Soo Kim5Department of Mechanical Engineering, Dongguk University, Seoul 04620, Republic of KoreaDepartment of Mechanical Engineering, Dongguk University, Seoul 04620, Republic of KoreaDepartment of Mechanical Engineering, Dongguk University, Seoul 04620, Republic of KoreaDepartment of Mechanical Engineering, Dongguk University, Seoul 04620, Republic of KoreaDepartment of Mechanical, Robotics and Energy Engineering, Dongguk University, Seoul 04620, Republic of KoreaDepartment of Mechanical, Robotics and Energy Engineering, Dongguk University, Seoul 04620, Republic of KoreaStructural 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.https://www.mdpi.com/2076-3417/14/23/11091structural health monitoringultrasonic techniqueslaminated composite structuresnon-destructive testingmachine learning |
| spellingShingle | Mohad Tanveer Muhammad Umar Elahi Jaehyun Jung Muhammad Muzammil Azad Salman Khalid Heung Soo Kim Recent Advancements in Guided Ultrasonic Waves for Structural Health Monitoring of Composite Structures Applied Sciences structural health monitoring ultrasonic techniques laminated composite structures non-destructive testing machine learning |
| title | Recent Advancements in Guided Ultrasonic Waves for Structural Health Monitoring of Composite Structures |
| title_full | Recent Advancements in Guided Ultrasonic Waves for Structural Health Monitoring of Composite Structures |
| title_fullStr | Recent Advancements in Guided Ultrasonic Waves for Structural Health Monitoring of Composite Structures |
| title_full_unstemmed | Recent Advancements in Guided Ultrasonic Waves for Structural Health Monitoring of Composite Structures |
| title_short | Recent Advancements in Guided Ultrasonic Waves for Structural Health Monitoring of Composite Structures |
| title_sort | recent advancements in guided ultrasonic waves for structural health monitoring of composite structures |
| topic | structural health monitoring ultrasonic techniques laminated composite structures non-destructive testing machine learning |
| url | https://www.mdpi.com/2076-3417/14/23/11091 |
| work_keys_str_mv | AT mohadtanveer recentadvancementsinguidedultrasonicwavesforstructuralhealthmonitoringofcompositestructures AT muhammadumarelahi recentadvancementsinguidedultrasonicwavesforstructuralhealthmonitoringofcompositestructures AT jaehyunjung recentadvancementsinguidedultrasonicwavesforstructuralhealthmonitoringofcompositestructures AT muhammadmuzammilazad recentadvancementsinguidedultrasonicwavesforstructuralhealthmonitoringofcompositestructures AT salmankhalid recentadvancementsinguidedultrasonicwavesforstructuralhealthmonitoringofcompositestructures AT heungsookim recentadvancementsinguidedultrasonicwavesforstructuralhealthmonitoringofcompositestructures |