16 May 2008 Smart sensors for the petroleum sector based on long period gratings supervised by artificial neural networks
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Proceedings Volume 7004, 19th International Conference on Optical Fibre Sensors; 70045W (2008) https://doi.org/10.1117/12.786843
Event: 19th International Conference on Optical Fibre Sensors, 2008, Perth, WA, Australia
Abstract
This work shows the use of long period gratings in the petroleum sector, in two specific applications. The proposed sensors are employed both to identify substances in a simulated flow inside a pipeline, and to assess the gasoline conformity commercialized in gas stations. The gratings responses for each specific case were employed to train and to validate two different topologies of artificial neural networks: perceptron multilayer and radial base function. The obtained results show that fiber optic sensors supervised by artificial neural networks can constitute systems for smart measurement with high applicability in the petrochemical field.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gustavo R. C. Possetti, Gustavo R. C. Possetti, Francelli K. Coradin, Francelli K. Coradin, Lílian C. Côcco, Lílian C. Côcco, Carlos I. Yamamoto, Carlos I. Yamamoto, Lucia V. R. de Arruda, Lucia V. R. de Arruda, Rosane Falate, Rosane Falate, Marcia Muller, Marcia Muller, José L. Fabris, José L. Fabris, } "Smart sensors for the petroleum sector based on long period gratings supervised by artificial neural networks", Proc. SPIE 7004, 19th International Conference on Optical Fibre Sensors, 70045W (16 May 2008); doi: 10.1117/12.786843; https://doi.org/10.1117/12.786843
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