Damage identification on composite materials | A Neural Networking process for fiber reinforced composite materials micro mechanical acoustic emission signatures

Carlos Rafael Ramirez Jimenez

ISBN 10: 3846539767 / ISBN 13: 9783846539767

Published by LAP LAMBERT Academic Publishing, 2011

About this Item

Damage identification on composite materials | A Neural Networking process for fiber reinforced composite materials micro mechanical acoustic emission signatures | Carlos Rafael Ramirez Jimenez | Taschenbuch | 312 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846539767 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand.

Seller Inventory # 106736406

Bibliographic Details

• Title: Damage identification on composite materials | A Neural Networking process for fiber reinforced composite materials micro mechanical acoustic emission signatures
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2011
• Language: English
• ISBN 10: 3846539767
• ISBN 13: 9783846539767
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 20D millimeters 220 millimeters width by 150 millimeters height by 20 millimeters depth
• Weight: 483 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

This book presents a reliable correlation between micro-mechanical failure events on fibre reinforced composite materials and their acoustic emission (AE) signature. Several fields of knowledge were involved on the research behind this book, for instance, composites theory was applied on the manufacturing of the testing coupons and the understanding of the micro-mechanical failure modes, ultrasound theory for the understanding of generation, transmission and recording of waveforms on composite materials. Finally, artificial neural networks for the classification and clustering of AE events recorded from the material. During pilot testing, the characterization of the recording system was defined, along with the study of the testing settings and physical factors that influence frequency response from fibre reinforced composite materials. The post analysis for each test involved the extraction and classification of the first and second highest frequencies by means of a self-organizing map algorithm. The resulting plots from this analysis showed 5 different classes of acoustic emission events; each class was successfully correlated to a different micro-mechanical event.

About the Author

The author has pursued a professional career in the field of Composite Materials at assorted institutions. He was a research engineer at Warwick University in the UK, also a researcher at UAM-I Mexico, then he joined the Wind Energy business as a design engineer and recently he moved to Aviation, both for General Electric in Queretaro, Mexico.