Intelligent Fiber Optic Sensor for Estimating the Concentration of a Mixture-Design and Working Principle

This paper presents the construction and working principles of an intelligent fiber-optic intensity sensor used for examining the concentration of a mixture in conjunction with water. It can find applications e.g. in waste-water treatment plant for selection of a treatment process. The sensor head i...

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Main Author: Michal Borecki
Format: Article
Language:English
Published: MDPI AG 2007-03-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/7/3/384/
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spelling doaj-0f0a06454f2e4a72a0761bd8cac76f312020-11-24T21:10:35ZengMDPI AGSensors1424-82202007-03-017338439910.3390/s7030384Intelligent Fiber Optic Sensor for Estimating the Concentration of a Mixture-Design and Working PrincipleMichal BoreckiThis paper presents the construction and working principles of an intelligent fiber-optic intensity sensor used for examining the concentration of a mixture in conjunction with water. It can find applications e.g. in waste-water treatment plant for selection of a treatment process. The sensor head is the end of a large core polymer optical fiber, which constitutes one arm of an asymmetrical coupler. The head works on the reflection intensity basis. The reflected signal level depends on the Fresnel reflection from the air and from the mixture examined when the head is immersed in it. The sensor head is mounted on a lift. For detection purposes the signal can be measured on head submerging, submersion, emerging and emergence. Therefore, the measured signal depends on the surface tension, viscosity, turbidity and refraction coefficient of the solution. The signal coming from the head is processed electrically in an opto-electronic interface. Then it is fed to a neural network. The novelty of the proposed sensor lies in that it contains an asymmetrical coupler and a neural network that works in the generalization mode. The sensor resolution depends on the efficiency of the asymmetrical coupler, the precision of the opto-electronic signal conversion and the learning accuracy of the neural network. Therefore, the number and quality of the points used for the learning process is very important. By way of example, the paper describes a sensor intended for examining the concentration of liquid soap in water.http://www.mdpi.com/1424-8220/7/3/384/opto-electronicfiber opticintensity sensor.
collection DOAJ
language English
format Article
sources DOAJ
author Michal Borecki
spellingShingle Michal Borecki
Intelligent Fiber Optic Sensor for Estimating the Concentration of a Mixture-Design and Working Principle
Sensors
opto-electronic
fiber optic
intensity sensor.
author_facet Michal Borecki
author_sort Michal Borecki
title Intelligent Fiber Optic Sensor for Estimating the Concentration of a Mixture-Design and Working Principle
title_short Intelligent Fiber Optic Sensor for Estimating the Concentration of a Mixture-Design and Working Principle
title_full Intelligent Fiber Optic Sensor for Estimating the Concentration of a Mixture-Design and Working Principle
title_fullStr Intelligent Fiber Optic Sensor for Estimating the Concentration of a Mixture-Design and Working Principle
title_full_unstemmed Intelligent Fiber Optic Sensor for Estimating the Concentration of a Mixture-Design and Working Principle
title_sort intelligent fiber optic sensor for estimating the concentration of a mixture-design and working principle
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2007-03-01
description This paper presents the construction and working principles of an intelligent fiber-optic intensity sensor used for examining the concentration of a mixture in conjunction with water. It can find applications e.g. in waste-water treatment plant for selection of a treatment process. The sensor head is the end of a large core polymer optical fiber, which constitutes one arm of an asymmetrical coupler. The head works on the reflection intensity basis. The reflected signal level depends on the Fresnel reflection from the air and from the mixture examined when the head is immersed in it. The sensor head is mounted on a lift. For detection purposes the signal can be measured on head submerging, submersion, emerging and emergence. Therefore, the measured signal depends on the surface tension, viscosity, turbidity and refraction coefficient of the solution. The signal coming from the head is processed electrically in an opto-electronic interface. Then it is fed to a neural network. The novelty of the proposed sensor lies in that it contains an asymmetrical coupler and a neural network that works in the generalization mode. The sensor resolution depends on the efficiency of the asymmetrical coupler, the precision of the opto-electronic signal conversion and the learning accuracy of the neural network. Therefore, the number and quality of the points used for the learning process is very important. By way of example, the paper describes a sensor intended for examining the concentration of liquid soap in water.
topic opto-electronic
fiber optic
intensity sensor.
url http://www.mdpi.com/1424-8220/7/3/384/
work_keys_str_mv AT michalborecki intelligentfiberopticsensorforestimatingtheconcentrationofamixturedesignandworkingprinciple
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