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Neural Network Processing of Optical Fiber Sensor Signals for Impact Location

  • Paul M. Schindler (a1), John K. Shaw (a2), Russell G. May (a1) and Richard O. Claus (a1)

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.

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1. Gunther, M.F., Wang, A., Fogg, B.R., Starr, S.E., Murphy, K.A., and Claus, R.O.: “Fiber optic impact detection and location system embedded in a composite material,” SPIE, Boston, September 1992.
2. Murphy, K., Gunther, M., Vengsarkar, A., and Claus, R.: “Quadrature phase-shifted, extrinsic Fabry-Perot optical fiber sensors,” Optics Letters, Vol. 16, No. 4, February 1991.
3. NeuralWare: “Using NeuralWorks,” NeuralWorks Professional II/PLUS software package (NeuralWare Inc., Pittsburgh, PA 15276, 1993), p. 20.
4. Sirkis, J.S., Shaw, K., Berkoff, T.A., Kersey, A.D., Friebele, E.J., and Jones, R.T.: “Development of an Impact Detection Technique Using Optical Fiber Sensors and Neural Networks,” SPIE #2191, pp. 158165.

Neural Network Processing of Optical Fiber Sensor Signals for Impact Location

  • Paul M. Schindler (a1), John K. Shaw (a2), Russell G. May (a1) and Richard O. Claus (a1)

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