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Item type:Research Data, Access status: with files , Supplementary Data for the Paper: “Data-Driven Localization of Magneto-Mechanical Resonators from Time Signals”(2026-09-07); ; ; ; This dataset provides the materials necessary to reproduce the paper "Data-Driven Localization of Magneto-Mechanical Resonators from Time Signals". It includes simulated data and background noise to reproduce the training and real measurements, with ground truth to infer the provided model.Data Type: Dataset30 50 - Some of the metrics are blocked by yourconsent settings
Item type:Research Data, Access status: with files , Supplementary Data for Natural Frequency Dependence of Magneto-Mechanical Resonators on Magnet Distance(2026-05-12); ; ; ; This dataset contains the raw data underlying the results presented in the research article "Natural Frequency Dependence of Magneto-Mechanical Resonators on Magnet Distance" (https://doi.org/10.1109/JSEN.2025.3600007) from J. Faltinath, F. Mohn, F. Foerger, M. Möddel and T. Knopp published in the IEEE Sensors Journal, Volume 25, Issue 20.Data Type: Experimental Data62 14 - Some of the metrics are blocked by yourconsent settings
Item type:Research Data, Access status: with files , Supplementary Data for the Publication: Parameter Estimation for Model-Based Sensing of Magneto-Mechanical Resonators(2026-02-23); ; ; ; 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.Data Type: Experimental Data81 98 - Some of the metrics are blocked by yourconsent settings
Item type:Research Data, Access status: with files , Data supplement for publication: Wireless and passive pressure detection using magneto-mechanical resonances in process engineering(2025-07-29); ; ; ; The TUHH Open Research (TORE) repository entails the raw files and the result files for the publication "Wireless and passive pressure detection using magneto-mechanical resonances in process engineering". A custom-developed magneto-mechanical resonator (MMR) for wireless pressure measurement is investigated for potential applications in process engineering. The MMR sensor utilises changes in the resonance frequency caused by pressure on a flexible 3D printed membrane. The thickness of the printed membrane plays a crucial role in determining the performance and sensitivity of MMRs, and can be tailored to meet the requirements of specific applications. The study includes static and dynamic measurements to determine the pressure sensitivity and temporal resolution of the sensor. The results show a minimum sensitivity of 0.06 Hz/mbar and are in agreement with theoretical calculations and measurements. The maximum sensor readout frequency is 2 Hz in this study. Additionally, the temperature dependence of the sensor is investigated, revealing a significant dependence of the resonance frequency on temperature. The developed MMR offers a promising and versatile method for precise pressure measurements in process engineering environments.Data Type: Experimental Data169 181