PSI - Issue 54

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ScienceDirect

Procedia Structural Integrity 54 (2024) 225–232 Structural Integrity Procedia 00 (2023) 000–000 Structural Integrity Procedia 00 (2023) 000–000

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© 2023 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 the scientific committee of the ICSI 2023 organizers © 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 the scientific committee of the ICSI 2023 organizers. Keywords: Acoustic Emission; Akaike Information Criterion; Time of Arrival; Syntactic Foams; Cenosphere Abstract Innovation in material science and the introduction of new structural materials into the commercial and industrial market are forcing researchers to look for modern, sophisticated and advanced structural monitoring tools. The Acoustic Emission (AE) technique is one of the most widely used Structural Health Monitoring (SHM) tools. Despite its remarkable advantages over all other passive Non-Destructive Evaluation (NDE) tools, its applicability is constantly being questioned. This is due to the complex time-frequency characteristics of acoustic waves, especially when used in highly noisy environments or highly non-homogeneous structures. In this study, an advanced signal processing technique is used to analyse the acoustic signals generated by di ff erent failure modes of composite specimens. A novel procedure is proposed to extract the Time of Arrival (ToA) of the AE signals. This approach uses a modified version of the Akaike Information Criterion (AIC), which is applicable also to signals with a low signal-to-noise ratio. The proposed method is tested on the AE signals generated from the static tensile test of the syntactic foam, cenosphere-reinforced unsaturated polyester composites. The ToA of the AE signals successfully identifies the damage evolution stages in the syntactic foam. © 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 the scientific committee of the ICSI 2023 organizers. Keywords: Acoustic Emission; Akaike Information Criterion; Time of Arrival; Syntactic Foams; Cenosphere International Conference on Structural Integrity 2023 (ICSI 2023) Advanced Acoustic Emission Signal Processing Techniques for Structural Health Monitoring Claudia Barile a , Vimalathithan Paramsamy Kannan a, ∗ , Giovanni Pappalettera a , Caterina Casavola a a Dipartimento di Meccanica, Matematica e Management, Politecnico di Bari, Via E.Orabona 4, 70125 - Bari, Italy Abstract Innovation in material science and the introduction of new structural materials into the commercial and industrial market are forcing researchers to look for modern, sophisticated and advanced structural monitoring tools. The Acoustic Emission (AE) technique is one of the most widely used Structural Health Monitoring (SHM) tools. Despite its remarkable advantages over all other passive Non-Destructive Evaluation (NDE) tools, its applicability is constantly being questioned. This is due to the complex time-frequency characteristics of acoustic waves, especially when used in highly noisy environments or highly non-homogeneous structures. In this study, an advanced signal processing technique is used to analyse the acoustic signals generated by di ff erent failure modes of composite specimens. A novel procedure is proposed to extract the Time of Arrival (ToA) of the AE signals. This approach uses a modified version of the Akaike Information Criterion (AIC), which is applicable also to signals with a low signal-to-noise ratio. The proposed method is tested on the AE signals generated from the static tensile test of the syntactic foam, cenosphere-reinforced unsaturated polyester composites. The ToA of the AE signals successfully identifies the damage evolution stages in the syntactic foam. International Conference on Structural Integrity 2023 (ICSI 2023) Advanced Acoustic Emission Signal Processing Techniques for Structural Health Monitoring Claudia Barile a , Vimalathithan Paramsamy Kannan a, ∗ , Giovanni Pappalettera a , Caterina Casavola a a Dipartimento di Meccanica, Matematica e Management, Politecnico di Bari, Via E.Orabona 4, 70125 - Bari, Italy

1. Introduction 1. Introduction

The Acoustic Emission (AE) technique is considered as one of the most formidable Nondestructive Evaluation (NDE) for structural health monitoring. Since its introduction in the 1960s, its definitions, use and applications have been documented by several researchers [Sause et al. (2012), Barile et al. (2020)]. In short, in this technique, the stress waves generated by a material / structure undergoing deformation due to external forces are used to analyse the characteristics of the deforming material / structure. The stress waves are analysed in two ways: parameter-based anal ysis and signal-based analysis. The parameter-based analysis is useful for in-situ analysis while serving as a passive The Acoustic Emission (AE) technique is considered as one of the most formidable Nondestructive Evaluation (NDE) for structural health monitoring. Since its introduction in the 1960s, its definitions, use and applications have been documented by several researchers [Sause et al. (2012), Barile et al. (2020)]. In short, in this technique, the stress waves generated by a material / structure undergoing deformation due to external forces are used to analyse the characteristics of the deforming material / structure. The stress waves are analysed in two ways: parameter-based anal ysis and signal-based analysis. The parameter-based analysis is useful for in-situ analysis while serving as a passive

∗ Corresponding author. Vimalathithan Paramsamy Kannan E-mail address: pk.vimalathithan@poliba.it ∗ Corresponding author. Vimalathithan Paramsamy Kannan E-mail address: pk.vimalathithan@poliba.it

2452-3216 © 2023 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 the scientific committee of the ICSI 2023 organizers 10.1016/j.prostr.2024.01.077 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 the scientific committee of the ICSI 2023 organizers. 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 the scientific committee of the ICSI 2023 organizers.