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Proceedings Paper

Artificial intelligence for identifying impacts on smart composites
Author(s): Qingshan Shan; Graham King; John Savage
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Paper Abstract

This paper present a methodology for impact identification on smart composites. The methodology is composed of four major parts: smart structures for detecting impact to composite; the cross correlation process; feature extraction and adaptive neuro fuzzy inference system (ANFIS) for identifying impacts. The smart structure comprises two piezoelectric transducers embedded in a composite specimen. These are used to measure impact signals caused by foreign object impacts. The impact signals are processed with a cross correlation algorithm and show very clean and meaningful variations in amplitude and shape with differing impact events. Signal features are extracted from the cross correlation results and are processed by methods of mean, standard deviation, kurosis and skewness. The ANFISs are trained, checked, and tested with the feature data to identify abscissas of impact location, ordinates of impact location, and impact magnitude. There are two new aspects to have been developed in this study. The results of implementing the system are discussed and conclusions drawn.

Paper Details

Date Published: 10 July 2002
PDF: 8 pages
Proc. SPIE 4693, Smart Structures and Materials 2002: Modeling, Signal Processing, and Control, (10 July 2002); doi: 10.1117/12.475254
Show Author Affiliations
Qingshan Shan, Southampton Institute (United Kingdom)
Graham King, Southampton Institute (United Kingdom)
John Savage, Aerostructures Hamble, Ltd. (United Kingdom)

Published in SPIE Proceedings Vol. 4693:
Smart Structures and Materials 2002: Modeling, Signal Processing, and Control
Vittal S. Rao, Editor(s)

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