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Damage detection in composite materials using airborne acoustics

Pearson, Matthew R., Eaton, Mark Jonathan, Szigeti, Eszter, Pullin, Rhys, Clarke, Alastair, Burguete, Richard and Featherston, Carol Ann 2013. Damage detection in composite materials using airborne acoustics. Key Engineering Materials 569-57 , pp. 72-79. 10.4028/www.scientific.net/KEM.569-570.72

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Abstract

Composite materials are increasingly being used in a wide range of structural applications in place of metallic materials. This presents a new range of challenges when considering the monitoring of damage and failure in complex components. This paper explores these challenges and presents a potential monitoring method using airborne acoustics which is both non-contact and easily implemented. A carbon composite panel was manufactured and statically loaded in tension until failure. During the test, Digital Image Correlation (DIC) was used to measure full field surface strain in the panel. An array of microphones, placed adjacent to the panel, was used to capture airborne acoustic signals between 400Hz and 20kHz during the test. The captured sound waves potentially contain signals originating from a range of sources, such as fibre failures and matrix cracking, but also contain background noise. A range of techniques have been used to examine the signals and determine the onset of failure, including Short-Time Fourier Transforms (STFT). The detection of failure using the airborne acoustic system has been validated using the strain data from the DIC measurements. The results presented demonstrate the applicability of the airborne system to monitoring of composite components.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Engineering
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Uncontrolled Keywords: Audible Acoustics, Composites Structures, Damage Detection, Digital Image Correlation (DIC), Frequency Analysis
Publisher: Trans Tech Publications
ISSN: 1662-9795
Last Modified: 13 Nov 2019 00:43
URI: http://orca.cf.ac.uk/id/eprint/50041

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