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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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.
Creators(s): |
Graham, D. ![]() | Item type: | Article |
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ID code: | 17320 |
Keywords: | eddy current, neural network, composite laminates, Chemistry, Materials Science(all), Mechanical Engineering, Condensed Matter Physics |
Subjects: | Science > Chemistry |
Department: | Faculty of Science > Pure and Applied Chemistry Faculty of Science > Physics |
Depositing user: | Strathprints Administrator |
Date deposited: | 26 Apr 2010 10:31 |
Last modified: | 20 Jan 2021 18:27 |
URI: | https://strathprints.strath.ac.uk/id/eprint/17320 |
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