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Damage classification in carbon fibre composites using acoustic emission: A comparison of three techniques

McCrory, John P., Al-Jumaili, Safaa Kh., Crivelli, Davide ORCID:, Pearson, Matthew R. ORCID:, Eaton, Mark J. ORCID:, Featherston, Carol A. ORCID:, Guagliano, Mario, Holford, Karen M. ORCID: and Pullin, Rhys ORCID: 2015. Damage classification in carbon fibre composites using acoustic emission: A comparison of three techniques. Composites Part B: Engineering 68 , pp. 424-430. 10.1016/j.compositesb.2014.08.046

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Classifying the type of damage occurring within a structure using a structural health monitoring system can allow the end user to assess what kind of repairs, if any, that a component requires. This paper investigates the use of acoustic emission (AE) to locate and classify the type of damage occurring in a composite, carbon fibre panel during buckling. The damage was first located using a bespoke location algorithm developed at Cardiff University, called delta-T mapping. Signals identified as coming from the regions of damage were then analysed using three AE classification techniques; Artificial Neural Network (ANN) analysis, Unsupervised Waveform Clustering (UWC) and corrected Measured Amplitude Ratio (MAR). A comparison of results yielded by these techniques shows a strong agreement regarding the nature of the damage present in the panel, with the signals assigned to two different damage mechanisms, believed to be delamination and matrix cracking. Ultrasonic C-scan images and a digital image correlation (DIC) analysis of the buckled panel were used as validation. MAR’s ability to reveal the orientation of recorded signals greatly assisted the identification of the delamination region, however, ANN and UWC have the ability to group signals into several different classes, which would prove useful in instances where several damage mechanisms were generated. Combining each technique’s individual merits in a multi-technique analysis dramatically improved the reliability of the AE investigation and it is thought that this cross-correlation between techniques will also be the key to developing a reliable SHM system.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Publisher: Elsevier
ISSN: 1359-8368
Funders: EPSRC
Date of First Compliant Deposit: 30 March 2016
Date of Acceptance: 26 August 2014
Last Modified: 05 Jan 2024 06:13

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