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 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.

[1]  Michael J. Wilson Path integral model of light scattered by turbid media , 2000, Photonics West - Biomedical Optics.

[2]  Michal Borecki Light behaviour in polymer optical fibre bend – a new analysis method , 2003 .

[3]  James Eugene Klein Challenges and problems in nonsequential ray tracing , 2001, Optics + Photonics.

[4]  Anna Grazia Mignani,et al.  Fiber optic systems for colorimetry and scattered colorimetry , 2005, SPIE Optics + Optoelectronics.

[5]  Yi Zhang,et al.  An integrated fluorescence detection system for lab-on-a-chip applications. , 2007, Lab on a chip.

[6]  Ruikang K. Wang,et al.  A path-integral model of light scattered by turbid media , 2001 .

[7]  O. M. Conde,et al.  Selected R & D results of PEG-UC and trends of Photonics Sensing Technology ( invited paper ) , 2006 .

[8]  M. Teich,et al.  Fundamentals of Photonics , 1991 .

[9]  Plastic optical fiber builds on MOST success , 2006 .

[10]  Wojtek J. Bock,et al.  Application of photonic band gap fibers in capillary electrophoresis systems , 2005, SPIE Optics + Optoelectronics.

[11]  N. K. Bose,et al.  Neural Network Fundamentals with Graphs, Algorithms and Applications , 1995 .

[12]  Curtis F. Gerald Applied numerical analysis , 1970 .

[13]  Michal Borecki,et al.  Intelligent high resolution sensor for detecting of liquid mediums , 2001 .

[14]  Michal Borecki,et al.  Design and performance of the asymmetrical coupler of plastic optical fibers , 2004, Lightguides and Their Applications.