Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Statistics
  • Help & Advice
University of Warwick

The Library

  • Login

Discriminating fiber-reinforced plastic signatures related to specific failure mechanisms: using self-organizing maps and fuzzy C-Means

Tools
- Tools
+ Tools

Li, XuQin, Ramirez, Carlos, Hines, Evor L., Leeson, Mark S., 1963-, Purnell, Phil and Pharaoh, Mark W. (2008) Discriminating fiber-reinforced plastic signatures related to specific failure mechanisms: using self-organizing maps and fuzzy C-Means. In: Intelligent Systems: Techniques and Applications. Shaker Publishing, Maastricht, The Netherlands, pp. 249-286. ISBN 978-90-423-0345-4

Full text not available from this repository.
Official URL: http://www2.warwick.ac.uk/fac/sci/eng/staff/msl/pu...

Abstract

Acoustic Emission (AE) can be used to discriminate the different types of damage occurring in composite materials, because any AE signal contains useful information about the damage mechanisms. A major issue in the use of the AE technique is how to discriminate the AE signatures which are due to the different damage mechanisms. Conventional studies have focused on the analysis of different parameters of such signals, say the frequency. But in previous publications where the frequency is employed to differentiate between events, only one frequency is considered and this frequency was not enough to thoroughly describe the behavior of the composite material. So we introduced the second frequency. A fast Fourier transform (FFT) is then applied to the signals resulting from the two frequencies to discriminate different failure mechanisms. The data was then analyzed using self-organizing map (SOM) and fuzzy C-means (FCM). The results shows that the two approaches have been very successful in discriminating fiber-reinforced plastic signatures related to specific failure mechanisms.

Item Type: Book Item
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science > Engineering
Publisher: Shaker Publishing
Place of Publication: Maastricht, The Netherlands
ISBN: 978-90-423-0345-4
Book Title: Intelligent Systems: Techniques and Applications
Editor: Hines, Evor L. and Leeson, Mark S., 1963- and Martínez-Ramón, Manel and Pardo, Matteo and Llobet, Eduard and Iliescu, Daciana and Yang, Jianhua
Date: 2008
Number of Pages: 38
Page Range: pp. 249-286
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
URI: http://wrap.warwick.ac.uk/id/eprint/46508

Request changes to a record

Actions (login required)

View Item View Item
twitter

Email us: publications@warwick.ac.uk
Contact Details
About Us