The Library
Pattern recognition of fiber-reinforced plastic failure mechanism using computational intelligence techniques
Tools
Tools
Tools
Li, XuQin, Ramirez, Carlos, Hines, Evor, Leeson, Mark S., Purnell, Phil and Pharaoh, Mark W. (2008) Pattern recognition of fiber-reinforced plastic failure mechanism using computational intelligence techniques. In: International Joint Conference on Neural Networks, Hong Kong, China, Jun 01-08, 2008. Published in: Proceedings of the 2008 IEEE International Joint Conference on Neural Networks, Vol.1-8 pp. 2340-2345.
Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/IJCNN.2008.4634122
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. This was achieved by using self-organizing map and Fuzzy C-means to cluster the AE data. The result shows that the two approaches have been very successful.
| Item Type: | Conference Item (Paper) | ||||
|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering |
||||
| Divisions: | Faculty of Science > Engineering | ||||
| Series Name: | IEEE International Joint Conference on Neural Networks (IJCNN) | ||||
| Journal or Publication Title: | Proceedings of the 2008 IEEE International Joint Conference on Neural Networks | ||||
| Publisher: | Institute of Electrical and Electronic Engineers | ||||
| ISBN: | 978-1-4244-1820-6 | ||||
| ISSN: | 1098-7576 | ||||
| Official Date: | 2008 | ||||
| Dates: |
|
||||
| Volume: | Vol.1-8 | ||||
| Number of Pages: | 6 | ||||
| Page Range: | pp. 2340-2345 | ||||
| Identification Number: | 10.1109/IJCNN.2008.4634122 | ||||
| Status: | Not Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access | ||||
| Funder: | Warwick Postgraduate Research Fellowship (WPRF), Overseas Research Students Award Scheme (ORSAS) | ||||
| Conference Paper Type: | Paper | ||||
| Title of Event: | International Joint Conference on Neural Networks | ||||
| Type of Event: | Conference | ||||
| Location of Event: | Hong Kong, China | ||||
| Date(s) of Event: | Jun 01-08, 2008 | ||||
| URI: | http://wrap.warwick.ac.uk/id/eprint/28398 |
Data sourced from Thomson Reuters' Web of Knowledge
Request changes or add full text files to a record
Actions (login required)
 |
View Item |
