Design of Fluxgate Current Sensor Based on Magnetization Residence Times and Neural Networks

Design of Fluxgate Current Sensor Based on Magnetization Residence Times and Neural Networks

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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 ashy bines protein powder 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 iphone 14 price san francisco 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.