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Intelligent fiber optic statistical mode sensors using novel features and artificial neural networks

机译:利用新颖功能和人工神经网络的智能光纤统计模式传感器

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In this paper, intelligent statistical mode sensors are proposed and analyzed. Several statistical features are used in design of intelligent sensor systems. Force measurement experiments are conducted and experimental data is analyzed using newly proposed statistical features. After that, Artificial Neural Networks (ANNs) with sensor data fusion, which is an intelligent sensor architecture, was proposed to estimate the force values. Multilayer perceptron (MLP) with different algorithms are used in the ANN model, and all of them can predict the force values with acceptable error levels. Using sensor fusion with ANNs, statistical mode sensors can be calibrated and fault tolerance of the sensor can be decreased, hence more reliable intelligent sensors can be designed.
机译:本文提出和分析了智能统计模式传感器。智能传感器系统的设计中使用了几种统计特征。进行力测量实验,并使用新提出的统计特征分析实验数据。之后,提出了具有传感器数据融合的人工神经网络(ANN),这是智能传感器架构,以估计力值。在ANN模型中使用具有不同算法的多层的Perceptron(MLP),并且所有这些都可以预测具有可接受的误差水平的力值。使用带ANN的传感器融合,可以校准统计模式传感器,可以减少传感器的容错,因此可以设计更可靠的智能传感器。

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