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This paper presents multimode fiber optic sensors suitable for large smart structures where distributed sensing needed. By many observations of speckle patterns from different multimode fibers, it seems that each speckle pattern has its own signature and uniquely defines its fiber. This prompted us to superimpose (multiplexed) the speckle patterns generated by two different fibers, and detect the resultant pattern. A two-stage feature extraction algorithm is then applied on the image, which reduces the dimension of the pattern vector. Next, a backpropagation neural network with single hidden layer is trained in mapping the feature vectors to the stress applied on each fiber. Series of experiments are conducted on two fiber sensors glued on a square shape plate under different point loads. The sensors successfully estimated that which fiber was under stress with light or heavy weight.
Mohammed R. Sayeh,Lalit Gupta,D. Kagaris,R. Viswanathan, andB. Chung
"Multiplexed fiber optic strain sensors for distributed sensing", Proc. SPIE 4357, Distributed Fiber Optical Sensors and Measuring Networks, (23 February 2001); https://doi.org/10.1117/12.417877
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Mohammed R. Sayeh, Lalit Gupta, D. Kagaris, R. Viswanathan, B. Chung, "Multiplexed fiber optic strain sensors for distributed sensing," Proc. SPIE 4357, Distributed Fiber Optical Sensors and Measuring Networks, (23 February 2001); https://doi.org/10.1117/12.417877