Vibration Analysis using Extrinsic Fabry-Perot Interferometric Sensors and Neural Networks
An Extrinsic Fabry-Perot interferometric (EFPI) sensor attached to a vibrating structure will see a sinusoidal strain. Harmonic analysis on this strain yields well defined harmonics. Strain level measurement, on a periodically-actuated-instrumented structure, can provide information about the heath of that structure. This approach can form a smart health monitoring system for composite structures. A simple demodulation system employing artificial neural networks (ANN) was used to extract harmonics and predict the maximum strain level on a smart composite beam. This paper deals with the computer simulation of the sinusoidal strain and implementation of the demodulation system. The system employs two back-propagation neural networks. The first network extracts the harmonics from the strain profile and the second predicts the strain levels through harmonic analysis extracted.
R. Dua et al., "Vibration Analysis using Extrinsic Fabry-Perot Interferometric Sensors and Neural Networks," Intelligent Engineering Systems Through Artificial Neural Networks, American Society of Mechanical Engineers (ASME), Nov 2002.
Artificial Neural Networks in Engineering Conference, ANNIE 2002 (2002: Nov. 10-13, St. Louis, MO)
Electrical and Computer Engineering
Keywords and Phrases
Extrinsic Fabry-Perot Interferometric Sensor; Vibrating Structure; Harmonic analysis
Article - Conference proceedings
© 2002 American Society of Mechanical Engineers (ASME), All rights reserved.
13 Nov 2002