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The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including those from the School of Psychological Sciences & Health - but also papers by researchers based within the Faculties of Science, Engineering, Humanities & Social Sciences, and from the Strathclyde Business School.

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Impact damage detection in carbon fibre composites using HTS SQUIDs and neural networks

Graham, D. and Maas, P. and Donaldson, G.B. and Carr, C. (2004) Impact damage detection in carbon fibre composites using HTS SQUIDs and neural networks. NDT and E International, 37 (7). pp. 565-570. ISSN 0963-8695

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Abstract

A neural network-based data analysis tool, developed to speed the damage detection process for the NDE of impact damaged carbon fibre composites, is discussed. A feature extraction method utilising a gradient threshold search function and a feed forward neural network for pattern recognition were used to develop the system. Impact damaged carbon composite sample plates were scanned with an eddy current-based NDE setup using HTS SQUID gradiometers and double-D excitation coils. Detection of damage sites in data affected by noise spikes caused by environmental disturbances is demonstrated. Finally, a possible design for a future entirely automated scanning system is also introduced.