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Artificial Neural Networks based Approach for Predicting LVDT Output Characteristics

机译:基于人工神经网络的LVDT输出特性预测方法

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摘要

This paper presents a novel approach for training and output prediction of data of a Linear variable differential transformer (LVDT). LVDT is a commonly used device used in laboratories for measuring linear displacements in specific situations. This article considers application of Artificial Neural Networks (ANNs) for learning and output estimation of LVDT. Real-time experiments were conducted and results were collected for training of ANNs. The Regression results and outputs verified the learning and prediction capability of ANNs.
机译:本文提出了一种新颖的方法,用于训练和预测线性可变差动变压器(LVDT)的数据。 LVDT是实验室中常用的设备,用于在特定情况下测量线​​性位移。本文考虑了人工神经网络(ANN)在LVDT学习和输出估计中的应用。进行了实时实验,并收集了结果以用于人工神经网络的训练。回归结果和输出证明了人工神经网络的学习和预测能力。

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