The artificial neural network modelling of the piezoelectric actuator vibrations using laser displacement sensor

Levent Paralı; Ali Sarı; Ulaş Kılıç; Özge Şahin; Jiří Pěchoušek

doi:10.1515/jee-2017-0069

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The artificial neural network modelling of the piezoelectric actuator vibrations using laser displacement sensor

Journal of Electrical Engineering

Volume 68 (2017): Issue 5 (September 2017)

By: Levent Paralı, Ali Sarı, Ulaş Kılıç, Özge Şahin and Jiří Pěchoušek

Open Access

|Nov 2017

Abstract

We report an improvement of the artificial neural network (ANN) modelling of a piezoelectric actuator vibration based on the experimental data. The controlled vibrations of an actuator were obtained by utilizing the swept-sine signal excitation. The peak value in the displacement signal response was measured by a laser displacement sensor. The piezoelectric actuator was modelled in both linear and nonlinear operating range. A consistency from 90.3 up to 98.9% of ANN modelled output values and experimental ones was reached. The obtained results clearly demonstrate exact linear relationship between the ANN model and experimental values.

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Articles in this issue

DOI: https://doi.org/10.1515/jee-2017-0069 | Journal eISSN: 1339-309X | Journal ISSN: 1335-3632

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Language: English

Page range: 371 - 377

Submitted on: Jun 20, 2017

Published on: Nov 28, 2017

Published by: Slovak University of Technology in Bratislava

In partnership with: Paradigm Publishing Services

Publication frequency: 6 issues per year

Keywords:

piezoelectric actuator,

laser displacement sensor,

resonance frequency,

vibration displacement,

artificial neural network

Related subjects:

Engineering,

Introductions and overviews,

Engineering, other

© 2017 Levent Paralı, Ali Sarı, Ulaş Kılıç, Özge Şahin, Jiří Pěchoušek, published by Slovak University of Technology in Bratislava
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 68 (2017): Issue 5 (September 2017)