Options
Parameter estimation for model-based sensing of magneto-mechanical resonators
Citation Link: https://doi.org/10.15480/882.18767
Publikationstyp
Journal Article
Date Issued
2026-10-01
Sprache
English
Author(s)
TORE-DOI
Journal
Volume
9
End Page
312
Citation
Communications Physics 9: 312 (2026)
Publisher DOI
Publisher
Springer
Peer Reviewed
true
Magneto-mechanical resonators (MMRs) 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 themodel 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.
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 themodel 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
physics.app-ph
DDC Class
616: Diseases
Publication version
publishedVersion
Loading...
Name
s42005-026-02884-1.pdf
Type
Main Article
Size
2.06 MB
Format
Adobe PDF