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  4. Supplementary Data for the Publication: Parameter Estimation for Model-Based Sensing of Magneto-Mechanical Resonators
 
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Supplementary Data for the Publication: Parameter Estimation for Model-Based Sensing of Magneto-Mechanical Resonators

Citation Link: https://doi.org/10.15480/882.16742
Type
Experimental Data
Date Issued
2026-02-23
Author(s)
Reiß, Sarah  orcid-logo
Biomedizinische Bildgebung E-5  
Knopp, Tobias  
Biomedizinische Bildgebung E-5  
Ackers, Justin  
Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering  
Faltinath, Jonas 
Biomedizinische Bildgebung E-5  
Mohn, Fabian  orcid-logo
Biomedizinische Bildgebung E-5  
Boberg, Marija  orcid-logo
Biomedizinische Bildgebung E-5  
Timm, Nora  
Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering  
Möddel, Martin  orcid-logo
Biomedizinische Bildgebung E-5  
Contact
Knopp, Tobias  
Biomedizinische Bildgebung E-5  
DOI
https://doi.org/10.15480/882.16742
TORE-URI
https://hdl.handle.net/11420/61653
Is Supplemented By
https://github.com/IBIResearch/MMR-Parameter-Estimation
Is Supplement To
10.48550/arXiv.2602.19965
Abstract
The TUHH Open Research (TORE) repository entails the experimental data of the paper "Parameter Estimation for Model-Based Sensing of Magneto-Mechanical Resonators".

Magneto-mechanical resonator (MMR) represent a recently proposed type of passive sensor that enables the estimation of its pose as well as sensing other parameters in its environment. The working principle of MMRs entails an excitation of the sensors by oscillating magnetic fields, followed by a readout process facilitated by inductive receiver coils. The sensing technology relies on real-time parameter estimation. This encompasses the solution of a nonlinear inverse problem, with the induced signals and a suitable forward model as inputs. The aim of this paper is twofold: first, to introduce a reference model and simplified models for the MMR dynamics and inductive readout, and second, to provide robust and real-time capable methods to estimate the model parameters. The effectiveness of the presented methods is evaluated in terms of their real-time potential, precision, and accuracy. All presented methods demonstrate the capacity to estimate the measured signal, with the simplified methods reducing the corresponding parameter estimation time by up to two orders of magnitude at the expense of less than 4 % deviation for large maximum deflection angles.
Subjects
magneto-mechanical resonator
model-based sensing
online parameter estimation
inverse problem
multi-component signal
DDC Class
629.8: Control and Feedback Control Systems
Funding(s)
SFB 1615 - SMARTe Reaktoren für die Verfahrenstechnik der Zukunft  
Funding Organisations
Deutsche Forschungsgemeinschaft (DFG)  
More Funding Information
This project is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – SFB 1615 – 503850735.
License
https://creativecommons.org/publicdomain/zero/1.0/
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Exp1_MMRL.h5

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250.05 MB

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