Compact optical particulate characterization based on a tapered-fiber bundle using a holographic ring-wedge detector and optical neural network

Martin S. Marshall

doi:10.1117/12.235659

15 March 1996 Compact optical particulate characterization based on a tapered-fiber bundle using a holographic ring-wedge detector and optical neural network

Martin S. Marshall

Author Affiliations +

Proceedings Volume 2752, Optical Pattern Recognition VII; (1996) https://doi.org/10.1117/12.235659
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

Abstract

A high-speed, compact optical correlation system is presented utilizing a tapered-fiber bundle, a holographic ring-wedge detector, and simple optical neural networks. This study includes three standard classes of unclassified military smokes and obscurants, standard liquid aerosol smokes, fibrous obscurants, and brass flakes. Digital and optical implementations of the holographic ring-wedge detector directly coupled into an optical neural network are studied as a means of increasing the speed of the decision process for particle characterization. This method has the ability to simultaneously recognize and distinguish the particle classes included in this study and to give a size range for spherical particles. Experimental data are presented utilizing a holographic ring detector and optical neural network combination for characterizing the particulates included in this study. A single holographic optical element fabricated to perform the same function as a ring detector and a simple two-layer, feedforward optical neural network are evaluated. Future work will include expanding the capabilities of the system to include more particulate types and to develop a field competent system.

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Martin S. Marshall "Compact optical particulate characterization based on a tapered-fiber bundle using a holographic ring-wedge detector and optical neural network", Proc. SPIE 2752, Optical Pattern Recognition VII, (15 March 1996); https://doi.org/10.1117/12.235659

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KEYWORDS

Particles

Sensors

Spherical lenses

Holography

Neural networks

Optical correlators

Holographic optical elements

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