Smart integrated-optics displacement/force sensor based on speckle pattern detection using neural-net with 0.1-A resolution

Umesh K. Rao; Augusto Garcia-Valenzuela; Massood Tabib-Azar

doi:10.1117/12.141229

2 March 1993 Smart integrated-optics displacement/force sensor based on speckle pattern detection using neural-net with 0.1-A resolution

Umesh K. Rao, Augusto Garcia-Valenzuela, Massood Tabib-Azar

Author Affiliations +

Proceedings Volume 1793, Integrated Optics and Microstructures; (1993) https://doi.org/10.1117/12.141229
Event: Fibers '92, 1992, Boston, MA, United States

Abstract

This paper describes the usage of neural networks in the application of speckle patterns, as seen at the output of an optical waveguide, for sensing displacement/force. The neural network trained for displacement values within a 1.5 micrometers range is found to generalize with less than +/- 0.02 micrometers error in the input range. It is found that a functional-link net with 11 functional links and 3 neurons can be trained for a convergence criterion of 1e-05 in less than 3000 iterations. The error in the individual targeted output during training was less than +/- 0.01 micrometers . Thus an integrated-optics sensor is now feasible.

Citation Download Citation

Umesh K. Rao, Augusto Garcia-Valenzuela, and Massood Tabib-Azar "Smart integrated-optics displacement/force sensor based on speckle pattern detection using neural-net with 0.1-A resolution", Proc. SPIE 1793, Integrated Optics and Microstructures, (2 March 1993); https://doi.org/10.1117/12.141229

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