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.

Meeting Name

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

Document Type

Article - Conference proceedings

Document Version


File Type





© 2002 American Society of Mechanical Engineers (ASME), All rights reserved.

Publication Date

13 Nov 2002

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