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- Title
Design of Fluxgate Current Sensor Based on Magnetization Residence Times and Neural Networks.
- Authors
Li, Jingjie; Ren, Wei; Luo, Yanshou; Zhang, Xutong; Liu, Xinpeng; Zhang, Xue
- Abstract
This study introduces a novel fluxgate current sensor with a compact, ring-shaped configuration that exhibits improved performance through the integration of magnetization residence times and neural networks. The sensor distinguishes itself with a unique magnetization profile, denoted as M waves, which emerge from the interaction between the target signal and ambient magnetic interference, effectively enhancing interference suppression. These M waves highlight the non-linear coupling between the magnetic field and magnetization residence times. Detection of these residence times is accomplished using full-wave rectification circuits and a Schmitt trigger, with a digital output provided by timing sequence detection. A dual-layer feedforward neural network deciphers the target signal, exploiting this non-linear relationship. The sensor achieves a linearity error of 0.054 % within a measurement range of 15 A. When juxtaposed with conventional sensors utilizing the residence-time difference strategy, our sensor reduces linearity error by more than 40-fold and extends the effective measurement range by 150 % . Furthermore, it demonstrates a significant decrease in ambient magnetic interference.
- Subjects
MAGNETIZATION; INTERFERENCE suppression; FEEDFORWARD neural networks; DETECTORS; NONLINEAR waves; MAGNETIC fields
- Publication
Sensors (14248220), 2024, Vol 24, Issue 12, p3752
- ISSN
1424-8220
- Publication type
Article
- DOI
10.3390/s24123752