Investigation of Dynamic Behavior of Smart Piezoelectric Actuators Using Artificial Neural Networks

The purpose of this study is to investigate microelectromechanical behavior of smart piezoelectric actuators using Artificial Neural Networks due to simple, multi harmonic and dynamic pulse excitations. Regarding to complexity and time-consuming analyses of vibration of smart structures, existing cl...

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Main Authors: Sepideh Ebrahimi, Somayyeh Shahbazi, Yaser Shahbazi, Ehsan Delavari
Format: Article
Language:English
Published: OICC Press 2024-02-01
Series:Majlesi Journal of Electrical Engineering
Subjects:
Online Access:https://oiccpress.com/mjee/article/view/5199
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author Sepideh Ebrahimi
Somayyeh Shahbazi
Yaser Shahbazi
Ehsan Delavari
author_facet Sepideh Ebrahimi
Somayyeh Shahbazi
Yaser Shahbazi
Ehsan Delavari
author_sort Sepideh Ebrahimi
collection DOAJ
description The purpose of this study is to investigate microelectromechanical behavior of smart piezoelectric actuators using Artificial Neural Networks due to simple, multi harmonic and dynamic pulse excitations. Regarding to complexity and time-consuming analyses of vibration of smart structures, existing classical models are often insufficient. Nowadays, artificial intelligence tools are used for modeling such complex phenomena. The theoretical model is a three-layer piezoelectric composite beam that behaves as an axial actuating mechanism. This actuator consists of an elastic core sandwiched between two piezoelectric active outer layers. The piezoelectric layers are polarized transversely, i.e., the polarization vector is parallel to the applied electric field intensity vector. For initializing the electromechanical effect, an electric field is applied to the piezoelectric layers. The finite element modeling is constructed using ANSYS. Then, harmonic and dynamic vibration analyses are performed and the responses of smart beam are calculated. The required data used for artificial intelligence were collected from vibration analyses. Obtained results demonstrate that artificial neural network is in good agreement with observed values.
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institution OA Journals
issn 2345-377X
2345-3796
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publishDate 2024-02-01
publisher OICC Press
record_format Article
series Majlesi Journal of Electrical Engineering
spelling doaj-art-834dfda00eaf4ac2a2f2f0d421aaf7de2025-08-20T02:15:58ZengOICC PressMajlesi Journal of Electrical Engineering2345-377X2345-37962024-02-0161Investigation of Dynamic Behavior of Smart Piezoelectric Actuators Using Artificial Neural NetworksSepideh Ebrahimi0Somayyeh Shahbazi1Yaser Shahbazi2Ehsan Delavari3Young Researchers Club, Islamic Azad University, Aligodarz Branch, AligodarzOmid Nahavand Higher Education/Electronic Group, Nahavand, IranSahand University of Technology/ Civil Department, Tabriz, IranSahand University of Technology/ Civil Department, Tabriz, IranThe purpose of this study is to investigate microelectromechanical behavior of smart piezoelectric actuators using Artificial Neural Networks due to simple, multi harmonic and dynamic pulse excitations. Regarding to complexity and time-consuming analyses of vibration of smart structures, existing classical models are often insufficient. Nowadays, artificial intelligence tools are used for modeling such complex phenomena. The theoretical model is a three-layer piezoelectric composite beam that behaves as an axial actuating mechanism. This actuator consists of an elastic core sandwiched between two piezoelectric active outer layers. The piezoelectric layers are polarized transversely, i.e., the polarization vector is parallel to the applied electric field intensity vector. For initializing the electromechanical effect, an electric field is applied to the piezoelectric layers. The finite element modeling is constructed using ANSYS. Then, harmonic and dynamic vibration analyses are performed and the responses of smart beam are calculated. The required data used for artificial intelligence were collected from vibration analyses. Obtained results demonstrate that artificial neural network is in good agreement with observed values.https://oiccpress.com/mjee/article/view/5199Artificial Neural NetworksHarmonic and Dynamic Vibration. Aligodarz branchIslamic Azad UniversityPiezoelectric actuatorsYoung Researchers Club
spellingShingle Sepideh Ebrahimi
Somayyeh Shahbazi
Yaser Shahbazi
Ehsan Delavari
Investigation of Dynamic Behavior of Smart Piezoelectric Actuators Using Artificial Neural Networks
Majlesi Journal of Electrical Engineering
Artificial Neural Networks
Harmonic and Dynamic Vibration. Aligodarz branch
Islamic Azad University
Piezoelectric actuators
Young Researchers Club
title Investigation of Dynamic Behavior of Smart Piezoelectric Actuators Using Artificial Neural Networks
title_full Investigation of Dynamic Behavior of Smart Piezoelectric Actuators Using Artificial Neural Networks
title_fullStr Investigation of Dynamic Behavior of Smart Piezoelectric Actuators Using Artificial Neural Networks
title_full_unstemmed Investigation of Dynamic Behavior of Smart Piezoelectric Actuators Using Artificial Neural Networks
title_short Investigation of Dynamic Behavior of Smart Piezoelectric Actuators Using Artificial Neural Networks
title_sort investigation of dynamic behavior of smart piezoelectric actuators using artificial neural networks
topic Artificial Neural Networks
Harmonic and Dynamic Vibration. Aligodarz branch
Islamic Azad University
Piezoelectric actuators
Young Researchers Club
url https://oiccpress.com/mjee/article/view/5199
work_keys_str_mv AT sepidehebrahimi investigationofdynamicbehaviorofsmartpiezoelectricactuatorsusingartificialneuralnetworks
AT somayyehshahbazi investigationofdynamicbehaviorofsmartpiezoelectricactuatorsusingartificialneuralnetworks
AT yasershahbazi investigationofdynamicbehaviorofsmartpiezoelectricactuatorsusingartificialneuralnetworks
AT ehsandelavari investigationofdynamicbehaviorofsmartpiezoelectricactuatorsusingartificialneuralnetworks