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Estimation of piezoelectric material parameters of ring-shaped specimens

  • Olga Friesen

    Olga Friesen is a research associate in the Measurement Engineering Group. After graduating in Electrical Engineering in 2022, she is now working on the quantitative characterisation of piezoelectric ceramics and the non-linear properties of these materials.

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    , Leander Claes

    Leander Claes graduated in Electrical Engineering in 2014. He has been a research associate since 2015, and deputy head of the Measurement Engineering Group since mid-2016. His research includes the development of acoustic measurement techniques with a focus on applications in material and fluid characterisation.

    , Nadine Feldmann

    Nadine Feldmann has been a research associate in the Measurement Engineering Group until November 2021. Her research fields included inverse measurement methods and characterisation of piezoelectric ceramics. She now works as a research engineer at Hesse GmbH in Paderborn.

    and Bernd Henning

    Bernd Henning is head of the Measurement Engineering Group, Faculty of Electrical Engineering, Computer Science and Mathematics at Paderborn University, Germany. His main areas of research are acoustic measurement procedures, ultrasonic and optical measurement engineering as well as biomedical measurement techniques.

Published/Copyright: January 8, 2025

Abstract

The estimation of accurate piezoelectric material parameters is a fundamental prerequisite for simulation-driven design of piezoelectric actuators and sensors. Previous studies show that a full set of material parameters can be determined in an inverse procedure using a single disc-shaped specimen with an electrode structured for increased sensitivity with respect to all material parameters. However, in the case of high-power actuator applications, ring-shaped piezoelectric components are often employed, necessitating an adaptation of the previously developed method. The alteration in geometry introduces some advantages. Accordingly, there is no longer any requirement to modify the electrode structure in order to enhance sensitivity. The method to estimate the material parameters presented here consists of a total of three stages. An initial, approximate estimation of the material parameters is determined using analytical approximations for the resonance frequencies from the IEEE standard. These values are optimised in an inverse procedure that employs analytic expressions for the electrical impedance of piezoelectric rings as the forward model. Further refinement is achieved by using Finite Element (FE) simulations as the forward model again in an inverse procedure. The method is applied to electrical impedance measurement data, yielding material parameters for hard piezoelectric rings. The result shows a good agreement between the simulation and measurement results, indicating realistic material parameter values.

Zusammenfassung

Die Schätzung präziser piezoelektrischer Materialparameter ist eine wichtige Voraussetzung für das simulationsgestützte Design piezoelektrischer Aktoren und Sensoren. Vorangegangene Studien zeigen, dass ein vollständiger Materialparametersatz in einem inversen Verfahren unter Verwendung einer einzelnen scheibenförmigen Probe mit einer strukturierten Elektrodentopologie, welche die Sensitivität der Impedanz in Bezug auf die Materialparameter erhöht, bestimmt werden kann. Bei Anwendungen für Hochleistungsaktoren werden jedoch häufig ringförmige piezoelektrische Komponenten verwendet, was eine Anpassung der zuvor entwickelten Methode erfordert. Die Änderung in der Geometrie bringt einige Vorteile mit sich. Dementsprechend ist eine Strukturierung der Elektroden zur Steigerung der Sensitivität nicht mehr notwendig. Die hier vorgestellte Methode zur Schätzung der Materialparameter umfasst insgesamt drei Schritte. Eine erste Schätzung der Materialparameter wird mithilfe der aus dem IEEE-Standard abgeleiteten, analytischen Näherungen für die Resonanzfrequenzen ermittelt. Diese Startwerte werden in einem inversen Verfahren optimiert, wobei analytische Ausdrücke für die elektrische Impedanz piezoelektrischer Ringe als Vorwärtsmodell verwendet werden. Eine weitere Optimierung wird durch die Verwendung von Finite-Elemente-Simulationen als Vorwärtsmodell, ebenfalls in einem inversen Verfahren, erreicht. Die Methode wird auf Messdaten einer elektrischen Impedanz angewendet, was zu vollständigen Materialparametersätzen für harte, piezoelektrische Ringe führt. Das Ergebnis zeigt eine gute Übereinstimmung zwischen den Simulations- und Messergebnissen, was auf realistische Parameterwerte hindeutet.


Corresponding author: Olga Friesen, Measurement Engineering Group, Paderborn University, Paderborn, Germany, E-mail: 

Award Identifier / Grant number: 444955436

About the authors

Olga Friesen

Olga Friesen is a research associate in the Measurement Engineering Group. After graduating in Electrical Engineering in 2022, she is now working on the quantitative characterisation of piezoelectric ceramics and the non-linear properties of these materials.

Leander Claes

Leander Claes graduated in Electrical Engineering in 2014. He has been a research associate since 2015, and deputy head of the Measurement Engineering Group since mid-2016. His research includes the development of acoustic measurement techniques with a focus on applications in material and fluid characterisation.

Nadine Feldmann

Nadine Feldmann has been a research associate in the Measurement Engineering Group until November 2021. Her research fields included inverse measurement methods and characterisation of piezoelectric ceramics. She now works as a research engineer at Hesse GmbH in Paderborn.

Bernd Henning

Bernd Henning is head of the Measurement Engineering Group, Faculty of Electrical Engineering, Computer Science and Mathematics at Paderborn University, Germany. His main areas of research are acoustic measurement procedures, ultrasonic and optical measurement engineering as well as biomedical measurement techniques.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: DeepL write: Enhance language.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: Deutsche Forschungsgemeinschaft (DFG) Projekt 444955436.

  7. Data availability: Not applicable.

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Received: 2024-11-18
Accepted: 2024-11-28
Published Online: 2025-01-08
Published in Print: 2025-06-26

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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