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Enlargement of Measurement Range in a Fiber-Optic Ice Sensor by Artificial Neural Network

机译:人工神经网络扩大光纤冰传感器的测量范围

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Artificial neural network (ANN) is employed to present a fiber-optic ice sensor (FOIS) with wide measurement range. Comparing with existing FOIS signal processing methods, this approach is not limited by the double-valued problem of output curve. Instead, it performs a measurement range from front-slope areas to back-slope areas. Moreover, this approach also handles the nonlinear problem of the sensor. As an application of the ANN, a calibration experiment platform is set up. The training samples are employed to train the ANN, and the testing samples are applied to surveil the predict ability of the ANN. The results obtained demonstrate the applicability of the proposed approach.
机译:人工神经网络(ANN)用于提供具有宽测量范围的光纤冰传感器(FOIS)。与现有的FOIS信号处理方法相比,该方法不受输出曲线双值问题的限制。而是执行从前斜坡区域到后斜坡区域的测量范围。此外,这种方法还可以处理传感器的非线性问题。作为人工神经网络的一种应用,建立了校准实验平台。训练样本被用来训练人工神经网络,测试样本被用来监视人工神经网络的预测能力。获得的结果证明了所提出方法的适用性。

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