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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| Format: | Article |
| Language: | English |
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OICC Press
2024-02-01
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| Series: | Majlesi Journal of Electrical Engineering |
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| 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. |
| format | Article |
| id | doaj-art-834dfda00eaf4ac2a2f2f0d421aaf7de |
| institution | OA Journals |
| issn | 2345-377X 2345-3796 |
| language | English |
| 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 |