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A novel multipoint luminescent coated ultra violet fibre sensor utilising artificial neural network pattern recognition techniques

机译:利用人工神经网络模式识别技术的新型多点发光涂层紫外光纤传感器

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摘要

A novel multipoint luminescent-coated optical fibre sensor system, which is capable of detecting ultra violet (UV) radiation and utilises artificial neural network (ANN) pattern recognition techniques to interpret its output is presented.The sensors of this investigation were fabricated on a 1mm core diameter polycarbonate fibre by removing sections of the fibre cladding and replacing it with a phosphor doped epoxy that emits visible light when stimulated with ultra violet radiation. The various sensing locations utilise phosphors that have different emission wavelengths resulting in individual spectral peaks associated with each of the sensing points. The system described is therefore capable of measuring levels of UV exposure at multiple points on a single fibre loop.The optical sensor system is interrogated using a fibre optic spectrometer, and the signal analysis of the data arising from the sensors is performed using artificial neural networks pattern recognition. This allows the interpretation and classification of the resulting complex spectral patterns, which contain spectral cross-coupling due to the phosphor emission overlap from the separate sensing points.Initial measurements were trained using a feed forward ANN, and the system was 100% successful in classification of all subsequent test samples analysed on the trained network, some of which are presented. (C) 2004 Elsevier B.V. All rights reserved.
机译:提出了一种新颖的多点发光涂层光纤传感器系统,该系统能够检测紫外线(UV)并利用人工神经网络(ANN)模式识别技术来解释其输出。本研究的传感器在1mm的直径上制造取下光纤包层的部分,并用磷光体掺杂的环氧树脂代替,将其制成直径中等的聚碳酸酯纤维,当受到紫外线辐射时,该环氧树脂会发出可见光。各个感测位置利用具有不同发射波长的磷光体,从而导致与每个感测点相关的各个光谱峰。因此,所描述的系统能够测量单个光纤环路上多个点的紫外线暴露水平。使用光纤光谱仪询问光学传感器系统,并使用人工神经网络对传感器数据进行信号分析模式识别。这使得可以解释和分类所产生的复杂光谱图,这些光谱图由于来自不同传感点的磷光体发射重叠而包含光谱交叉耦合。使用前馈ANN训练初始测量,该系统在分类​​中100%成功在经过训练的网络上分析的所有后续测试样本中,列出了其中的一些。 (C)2004 Elsevier B.V.保留所有权利。

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