Abstract
AbstractA 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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