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Neural Network Processing of Optical Fiber Sensor Signals for Impact Location

Published online by Cambridge University Press:  16 February 2011

Paul M. Schindler ,
John K. Shaw ,
Russell G. May  and
Richard O. Claus
Paul M. Schindler
Affiliation:
Fiber and Electro Optics Research Center, Department of Electrical Engineering, VirginiaTech, Blacksburg, VA 24061-0111
John K. Shaw
Affiliation:
Department of Mathematics, Virginia Tech, Blacksburg, VA 24061-0123
Russell G. May
Affiliation:
Fiber and Electro Optics Research Center, Department of Electrical Engineering, VirginiaTech, Blacksburg, VA 24061-0111
Richard O. Claus
Affiliation:
Fiber and Electro Optics Research Center, Department of Electrical Engineering, VirginiaTech, Blacksburg, VA 24061-0111
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Abstract

A system to detect and locate impacts by foreign bodies on a surface was developed and tested. Fiber optic extrinsic Fabry-Perot interferometer (EFPI) strain sensors were attached to or embedded in the surface, so that stress waves emanating from an impact could be detected. By employing an artificial neural network to process the sensor outputs, the impact location could be inferred to centimeter range accuracy directly from the arrival time data. In particular, the network could be trained to determine impact location regardless of material anisotropy. Results demonstrate that a back-propagation network identifiesimpact location for an anisotropic graphite/bismaleimide plate with the same accuracy as that for an isotropic aluminum plate.

Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 360 , 1994 , 121
Copyright
Copyright © Materials Research Society 1995

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References

references

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