PSI - Issue 80

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ScienceDirect

Procedia Structural Integrity 80 (2026) 93–104 Structural Integrity Procedia 00 (2023) 000–000 Structural Integrity Procedia 00 (2023) 000–000

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© 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Ferri Aliabadi © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review under responsibility of Professor Ferri Aliabadi. Keywords: Lamb wave imaging, Damage localization, MUSIC algorithm, MVDR algorithm; Abstract Lamb wave imaging is a promising technique for the structural health monitoring of composite plates, but the widely used Delay and-Sum (DAS) method often su ff ers from poor resolution and high levels of imaging artifacts, i.e. high sensitivity to noise. To overcome these limitations, advanced algorithms adapted from the field of Direction-of-Arrival (DOA) estimation can be employed. This paper provides a detailed comparison of the principles and performance of DAS, Minimum Variance Distortionless Response (MVDR), and Multiple Signal Classification (MUSIC) for localizing simulated damage on a quasi-isotropic composite plate. Since all three methods rely on the common ground of back-propagated scattered signals, this analysis aims to provide insights for developing novel damage imaging techniques. The key to improvement lies in finding e ff ective ways to suppress noise and artifacts, a primary strength of methods like MVDR, and this work suggests that extending other state-of-the-art DOA estimation methods to the damage imaging field is a promising avenue for future research. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review under responsibility of Professor Ferri Aliabadi. Keywords: Lamb wave imaging, Damage localization, MUSIC algorithm, MVDR algorithm; Abstract Lamb wave imaging is a promising technique for the structural health monitoring of composite plates, but the widely used Delay and-Sum (DAS) method often su ff ers from poor resolution and high levels of imaging artifacts, i.e. high sensitivity to noise. To overcome these limitations, advanced algorithms adapted from the field of Direction-of-Arrival (DOA) estimation can be employed. This paper provides a detailed comparison of the principles and performance of DAS, Minimum Variance Distortionless Response (MVDR), and Multiple Signal Classification (MUSIC) for localizing simulated damage on a quasi-isotropic composite plate. Since all three methods rely on the common ground of back-propagated scattered signals, this analysis aims to provide insights for developing novel damage imaging techniques. The key to improvement lies in finding e ff ective ways to suppress noise and artifacts, a primary strength of methods like MVDR, and this work suggests that extending other state-of-the-art DOA estimation methods to the damage imaging field is a promising avenue for future research. Fracture, Damage and Structural Health Monitoring Critical Assessment of Various Guided Wave Based Imaging Fracture, Damage and Structural Health Monitoring Critical Assessment of Various Guided Wave Based Imaging Damage Detection Algorithms Guangxiao Zou a , Zahra Sharif Khodaei a a Imperial College London, Exhibition Rd, South Kensington,London SW7 2AZ United Kingdom Damage Detection Algorithms Guangxiao Zou a , Zahra Sharif Khodaei a a Imperial College London, Exhibition Rd, South Kensington,London SW7 2AZ United Kingdom

1. Introduction 1. Introduction

Carbon Fiber Reinforced Polymer (CFRP) composites have been widely adopted in various industries and are valued for their exceptional strength-to-weight ratio, corrosion resistance, and long-term durability. However, their layered, anisotropic structure makes them susceptible to internal damage, particularly delamination, which can de velop due to low-velocity impact events, manufacturing imperfections, or operational fatigue. Because such subsur face damage is often invisible to the naked eye and can severely compromise the structural integrity of the material, the development of e ff ective real-time monitoring methods has become a critical priority. Among various non-destructive techniques, Lamb wave-based structural health monitoring has emerged as a particularly promising solution. The Carbon Fiber Reinforced Polymer (CFRP) composites have been widely adopted in various industries and are valued for their exceptional strength-to-weight ratio, corrosion resistance, and long-term durability. However, their layered, anisotropic structure makes them susceptible to internal damage, particularly delamination, which can de velop due to low-velocity impact events, manufacturing imperfections, or operational fatigue. Because such subsur face damage is often invisible to the naked eye and can severely compromise the structural integrity of the material, the development of e ff ective real-time monitoring methods has become a critical priority. Among various non-destructive techniques, Lamb wave-based structural health monitoring has emerged as a particularly promising solution. The

∗ Guangxiao Zou. Tel.: 44-07479622715; E-mail address: gz122@ic.ac.uk ∗ Guangxiao Zou. Tel.: 44-07479622715; E-mail address: gz122@ic.ac.uk

2452-3216 © 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Ferri Aliabadi 10.1016/j.prostr.2026.02.009 2210-7843 © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review under responsibility of Professor Ferri Aliabadi. 2210-7843 © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review under responsibility of Professor Ferri Aliabadi.