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  4. Contact Tip Trajectory in Steady-State Regime Prediction Using Deep Learning for Piezoelectric Actuators
 
conference paper

Contact Tip Trajectory in Steady-State Regime Prediction Using Deep Learning for Piezoelectric Actuators

Favier, Marc  
•
Liao, Xinxin  
•
Ghorbani, Marjan  
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2024
2024 27th International Conference on Electrical Machines and Systems, ICEMS 2024
27 International Conference on Electrical Machines and Systems

Including friction modeling in simulation can be challenging and requires time domain simulation, which is time consuming. We propose to separate the friction modelling from the FEA (Finite Element Analysis). The approach is defined for UCM (Ultrasonic Ceramic Motor) a type of piezoelectric actuator strongly relying on friction coupling between a vibrating tip and a sliding part. The tip's trajectory is studied both with and without contact. A DNN (Deep Neural Network) is trained to predict the contact trajectory from the contactless one, which can be obtained in frequency domain. Used as a complement of contact-free simulation of the UCM, the DNN can be used to predict the behavior of the complete actuator.

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Type
conference paper
DOI
10.23919/ICEMS60997.2024.10920910
Scopus ID

2-s2.0-105002378632

Author(s)
Favier, Marc  

École Polytechnique Fédérale de Lausanne

Liao, Xinxin  

École Polytechnique Fédérale de Lausanne

Ghorbani, Marjan  

École Polytechnique Fédérale de Lausanne

Germano, Paolo  

École Polytechnique Fédérale de Lausanne

Perriard, Yves  

École Polytechnique Fédérale de Lausanne

Date Issued

2024

Publisher

Institute of Electrical and Electronics Engineers Inc.

Published in
2024 27th International Conference on Electrical Machines and Systems, ICEMS 2024
ISBN of the book

9784886864406

Start page

3475

End page

3479

Subjects

contact modelling

•

deep learning

•

piezoelectric actuators

•

simulation

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LAI  
Event nameEvent acronymEvent placeEvent date
27 International Conference on Electrical Machines and Systems

ICEMS2024

Fukuoka, Japan

2024-11-26 - 2024-11-29

Available on Infoscience
April 29, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/249536
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