A method of examination of liquids by neural network analysis of reflectometric time domain data from optical capillaries and fibers

Michal Borecki; Michael L. Korwin-Pawlowski; Maria Beblowska

doi:10.1117/12.738651

2 July 2007 A method of examination of liquids by neural network analysis of reflectometric time domain data from optical capillaries and fibers

Michal Borecki, Michael L. Korwin-Pawlowski, Maria Beblowska

Author Affiliations +

Proceedings Volume 6619, Third European Workshop on Optical Fibre Sensors; 66193M (2007) https://doi.org/10.1117/12.738651
Event: Third European Workshop on Optical Fibre Sensors, 2007, Napoli, Italy

Abstract

This paper presents the construction and working principles of a reflectometric intelligent fiber-optic sensor used for liquid examination. Unlike other well-known fiber optical sensors which use information from optical wavelength variations, the proposed system uses time domain data. The sensing element consists of a length of optical fiber and a short section of optical capillary and works on the reflection intensity basis. The reflected signal level depends on the optical construction of the sensor element. The changes of the monitored signal are caused mainly by variation in light propagation conditions at the interfaces of liquid and gaseous phases. The physical effects involved are Fresnel reflection, local numerical aperture variation and liquid lenses formation. It is possible to call out across the changes of those effects by introducing a measuring procedure which includes submerging, submersion, emerging and emergence of the sensing head from the examined liquid or by local heating of the liquid sample.

Citation Download Citation

Michal Borecki, Michael L. Korwin-Pawlowski, and Maria Beblowska "A method of examination of liquids by neural network analysis of reflectometric time domain data from optical capillaries and fibers", Proc. SPIE 6619, Third European Workshop on Optical Fibre Sensors, 66193M (2 July 2007); https://doi.org/10.1117/12.738651

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