Neural network processor for n-mode fiber optic sensors

Howard Hou; Barry G. Grossman

doi:10.1117/12.152543

2 September 1993 Neural network processor for n-mode fiber optic sensors

Howard Hou, Barry G. Grossman

Proceedings Volume 1965, Applications of Artificial Neural Networks IV; (1993) https://doi.org/10.1117/12.152543
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

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.

Citation Download Citation

Howard Hou and Barry G. Grossman "Neural network processor for n-mode fiber optic sensors", Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); https://doi.org/10.1117/12.152543

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