DocumentCode :
1536969
Title :
Application of an Optical Fiber Sensor on the Determination of Sucrose and Ethanol Concentrations in Process Streams and Effluents of Sugarcane Bioethanol Industry
Author :
Fujiwara, Eric ; Ono, Eduardo ; Suzuki, Carlos Kenichi
Author_Institution :
Lab. of Photonic Mater. & Devices, State Univ. of Campinas, Campinas, Brazil
Volume :
12
Issue :
9
fYear :
2012
Firstpage :
2839
Lastpage :
2843
Abstract :
In this paper, the measurement of process streams and effluents from the sugar-ethanol industry using an optical fiber sensor based on the Fresnel reflection principle is reported. Firstly, binary sucrose-water and ethanol-water solutions with predetermined concentrations were measured for calibration purposes. Secondly, the coproducts from various processing stages were analyzed in order to identify the sucrose or ethanol content. The measured data were processed by an artificial neural network model, which correlated the reflected intensity values to the sample concentration. The absolute error was calculated by a comparison between the nominal concentration values obtained by the plant laboratory analysis and the sensor response, yielding errors ≤ 3& wt% and ≤ 5.1 vol% for the sucrose and ethanol contents, respectively. The fiber sensor has the potential to provide reliable results even for samples with more complex compositions than pure sucrose or ethanol solutions, with perspectives of application on the several stages of the plant facility.
Keywords :
biofuel; biotechnology; calibration; chemical sensors; chemical variables measurement; computerised instrumentation; fibre optic sensors; light reflection; neural nets; production engineering computing; sugar industry; Fresnel reflection principle; absolute error calculation; artificial neural network model; binary sucrose-water solution; calibration; ethanol concentration; ethanol-water solution; optical fiber sensor; plant laboratory analysis; process stream measurement; sucrose determination; sugarcane bioethanol industry; Artificial neural networks; Ethanol; Optical fiber networks; Optical fiber sensors; Optical fibers; Refractive index; Sugar; Bioethanol; chemical industry; optical fiber sensors; reflectometry; sugar industry;
fLanguage :
English
Journal_Title :
Sensors Journal, IEEE
Publisher :
ieee
ISSN :
1530-437X
Type :
jour
DOI :
10.1109/JSEN.2012.2204246
Filename :
6215009
Link To Document :
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