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

Full text not available in this repository.Request a copy from the Strathclyde author

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.

Creators(s): Graham, D. ORCID logoORCID: https://orcid.org/0000-0002-6079-2105, Maas, P., Donaldson, G.B. and Carr, C.;
Item type:Article
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
Export data:
CORE (COnnecting REpositories)