Artificial Neural Networks based Approach for Predicting LVDT Output Characteristics

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Author(s)

Ashwani Kharola 1,*

1. Department of Mechanical Engineering, Tula’s Institute, Dehradun-248197, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijem.2018.04.03

Received: 27 Mar. 2018 / Revised: 20 Apr. 2018 / Accepted: 16 May 2018 / Published: 8 Jul. 2018

Index Terms

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

Abstract

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.

Cite This Paper

Ashwani Kharola,"Artificial Neural Networks based Approach for Predicting LVDT Output Characteristic", International Journal of Engineering and Manufacturing(IJEM), Vol.8, No.4, pp.21-28, 2018. DOI: 10.5815/ijem.2018.04.03

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