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Interrogation of multipoint optical fibre sensor signals based on artificial neural network pattern recognition techniques

机译:基于人工神经网络模式识别技术的多点光纤传感器信号询问

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An optical fibre multipoint sensor system incorporating multiple (3) U-bend sensors is presented which is capable of detecting contaminants in water. The sensors are based on 62.5 mum core diameter polymer clad silicone (PCS) fibre which has had its cladding removed in the sensing regions. The addressing of the fibre is achieved using an optical time domain reflectometer (OTDR) and is, thus, capable of spatially resolving power loss (along the fibre's length). The signal analysis is performed using artificial neural networks (ANN) pattern recognition, which allows classification of the samples under test, thus, allowing the true measurand to be recognised. The system described is capable of both measurement at multiple points on a single fibre loop, and of recognising cross-sensitivity from interfering parameters such as lime scale coating in hard water and the presence of other species, e.g. alcohol in the water. Experimental results and the suitability of the ANN for their interpretation and classification are reported. (C) 2004 Elsevier B.V. All rights reserved.
机译:提出了一种包含多(3)个U形弯曲传感器的光纤多点传感器系统,该系统能够检测水中的污染物。传感器基于芯直径为62.5微米的聚合物包覆有机硅(PCS)光纤,该光纤的包覆层已在传感区域被移除。光纤的寻址是使用光时域反射仪(OTDR)实现的,因此能够在空间上解决功率损耗(沿着光纤的长度)。信号分析是使用人工神经网络(ANN)模式识别进行的,该模式识别可以对被测样品进行分类,从而可以识别出真实的被测量物。所描述的系统既能够在单根光纤环路上的多个点进行测量,又能够识别干扰参数的交叉敏感性,例如硬水中的水垢涂层以及是否存在其他物质,例如水垢。在水中的酒精。报告了实验结果以及人工神经网络对其解释和分类的适用性。 (C)2004 Elsevier B.V.保留所有权利。

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