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

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ABSTRACT

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.

No MeSH data available.


Flow chart of the simulation process.
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f3-sensors-07-00384: Flow chart of the simulation process.

Mentions: Therefore, the intensity version of the non- sequential ray tracing can be used, [8], for a design of the optical components or the sub-systems that utilize large core fibers and a multimode source. In this work we assume that, inside the fiber, the surface intensity distribution on a cross-section of the input tip of the optical components is uniform and the angular distribution is Gaussian [9]. Based on this information, meridional, skew and clad rays were generated. For the simulation purposes, we assumed that the initial number of rays is equal to 0.5% of the number of fiber modes. The proposed method utilizes the ray refraction and reflection according to the Fresnel phenomenon. The attenuation of the media was assumed to be constant. The internal light scattering in the fibers was neglected, but that in the liquid media was taken into account, [10]. The flow chart of the intensity method, which involves the estimation of the calculation tolerance aimed at reducing the simulation time, is shown in Figure 3.


Intelligent Fiber Optic Sensor for Estimating the Concentration of a Mixture-Design and Working Principle
Flow chart of the simulation process.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3756727&req=5

f3-sensors-07-00384: Flow chart of the simulation process.
Mentions: Therefore, the intensity version of the non- sequential ray tracing can be used, [8], for a design of the optical components or the sub-systems that utilize large core fibers and a multimode source. In this work we assume that, inside the fiber, the surface intensity distribution on a cross-section of the input tip of the optical components is uniform and the angular distribution is Gaussian [9]. Based on this information, meridional, skew and clad rays were generated. For the simulation purposes, we assumed that the initial number of rays is equal to 0.5% of the number of fiber modes. The proposed method utilizes the ray refraction and reflection according to the Fresnel phenomenon. The attenuation of the media was assumed to be constant. The internal light scattering in the fibers was neglected, but that in the liquid media was taken into account, [10]. The flow chart of the intensity method, which involves the estimation of the calculation tolerance aimed at reducing the simulation time, is shown in Figure 3.

View Article: PubMed Central

ABSTRACT

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.

No MeSH data available.