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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.


Relative value of the power in arm 2.
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f8-sensors-07-00384: Relative value of the power in arm 2.

Mentions: Examples of the thus-designed asymmetrical coupler were made manually by stripping off the polyethylene jacket, forming the curvature and polishing fibers. Then the fibers were positioned, etched and clamped. The relative coupling efficiency was:(7)u=P2P4+P2⋅100%,where: Pn is the power in arm n (Figure 4), shown in Figure 8.


Intelligent Fiber Optic Sensor for Estimating the Concentration of a Mixture-Design and Working Principle
Relative value of the power in arm 2.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3756727&req=5

f8-sensors-07-00384: Relative value of the power in arm 2.
Mentions: Examples of the thus-designed asymmetrical coupler were made manually by stripping off the polyethylene jacket, forming the curvature and polishing fibers. Then the fibers were positioned, etched and clamped. The relative coupling efficiency was:(7)u=P2P4+P2⋅100%,where: Pn is the power in arm n (Figure 4), shown in Figure 8.

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.