Intelligent fiber optic sensor for solution concentration examination

M. Borecki, J. Kruszewski
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引用次数: 1

Abstract

This paper presents the working principles of intelligent fiber-optic intensity sensor used for solution concentration examination. The sensor head is the ending of the large core polymer optical fiber. The head works on the reflection intensity basis. The reflected signal level depends on Fresnel reflection and reflection on suspended matter when the head is submersed in solution. The sensor head is mounted on a lift. For detection purposes the signal includes head submerging, submersion, emerging and emergence is measured. This way the viscosity turbidity and refraction coefficient has an effect on measured signal. The signal forthcoming from head is processed electrically in opto-electronic interface. Then it is feed to neural network. The novelty of presented sensor is implementation of neural network that works in generalization mode. The sensor resolution depends on opto-electronic signal conversion precision and neural network learning accuracy. Therefore, the number and quality of points used for learning process is very important. The example sensor application for examination of liquid soap concentration in water is presented in the paper.
用于溶液浓度检测的智能光纤传感器
本文介绍了用于溶液浓度检测的智能光纤强度传感器的工作原理。传感器头是大芯聚合物光纤的末端。头部根据反射强度工作。当头部浸入溶液时,反射信号电平取决于菲涅耳反射和悬浮物反射。传感器头安装在升降机上。为了检测目的,信号包括头浸入,浸入,出现和出现被测量。通过这种方式,粘度、浊度和折射系数对被测信号产生影响。在光电接口中对来自头部的信号进行电处理。然后将其输入神经网络。该传感器的新颖之处在于实现了神经网络的泛化模式。传感器的分辨率取决于光电信号转换精度和神经网络学习精度。因此,用于学习过程的点数的数量和质量是非常重要的。本文介绍了传感器在水中液皂浓度检测中的应用实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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