Abstract: The n-mode fiber optic sensor built has four linearly polarized (LP) modes propagating simultaneously in the fiber, producing a two-dimensional, spatially distributed output intensity pattern. When the fiber is strained, there is a change in fiber parameters. Oscillating and rotating of the pattern caused by coupling between degenerate modes is observed. Thus the processing of this type of output signal becomes one of a two- dimensional image processor. A neural network signal processor employing a back propagation algorithm was used in conjunction with the few mode fiber optic sensor to categorize the spatial output patterns from the sensor, thus converting the optical pattern to its corresponding strain value. The testing results show that the neural network processor is capable of recognizing this kind of image with good accuracy, resulting in strain accuracies within 0.7 percent.!13
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