Artificial neural networks based approach for predicting LVDT output characteristics

Artificial neural networks based approach for predicting LVDT output characteristics

Автор: Ashwani Kharola

Журнал: International Journal of Engineering and Manufacturing @ijem

Статья в выпуске: 4 vol.8, 2018 года.

Бесплатный доступ

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.

Artificial neural network, LVDT, Matlab, Simulink, Mean square error, Regression

Короткий адрес: https://sciup.org/15015853

IDR: 15015853   |   DOI: 10.5815/ijem.2018.04.03

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