Composite damage assessment employing an optical neural network processor and an embedded fiber-optic sensor array
Grossman, Barry G.
Thursby, Michael H.
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This paper discusses a novel approach for composite damage assessment with potential for DoD, NASA, and commercial applications. We have analyzed and modeled a two dimensional composite damage assessment system for real-time monitoring and determination of damage location in a composite structure. The system combines two techniques: a fiberoptic strain sensor array and an optical neural network processor. A two dimensional fiberoptic sensor array embedded in the composite structure during the manufacturing process can be used to detect changes in the mechanical strain distribution caused by subsequent damage to the structure. The optical processor, a pre-trained Kohonen neural network, has the capability to indicate the location of the damage due to its positionally associative architecture. Because of the parallel, all optical architecture of the system, the system has the advantages of having high resolution, a simple architecture, and almost instantaneous processor output. Results of the modeling and simulation predict a highly robust system with accurate determination of damage location. We are currently beginning work on a breadboard demonstration model of the system.