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Proceedings Paper

Application of neural networks to active damage detection technique of composites
Author(s): Lei Wang; Shenfang Yuan
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Paper Abstract

Cost-effective and reliable damage detection is critical for the utilization of composite materials. This paper applies a new combined method of Kohonen self-organizing feature neural networks and active damage detection technique to composite health monitoring. The proposed method features a simple structure algorithm, supervision free self-study and lateral association, etc. According to such method and virtual instrument technique, an active damage detection system for composites is developed. This effective method for damage detection has been verified in the course of its practical use.

Paper Details

Date Published: 29 April 2003
PDF: 7 pages
Proc. SPIE 5058, Optical Technology and Image Processing for Fluids and Solids Diagnostics 2002, (29 April 2003); doi: 10.1117/12.510320
Show Author Affiliations
Lei Wang, Nanjing Univ. of Aeronautics and Astronautics (China)
Shenfang Yuan, Nanjing Univ. of Aeronautics and Astronautics (China)


Published in SPIE Proceedings Vol. 5058:
Optical Technology and Image Processing for Fluids and Solids Diagnostics 2002
Gong Xin Shen; Soyoung S. Cha; Fu-Pen Chiang; Carolyn R. Mercer, Editor(s)

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