ArticleMicromachines2024
Optimization of Parameters and Comparison of Detection Signals for Planar Coil Particle Detection Sensors with Different Core Materials.
Article in Micromachines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Deep Neural Network-Based Design of Planar Coils for Proximity Sensing Applications.Sensors (Basel, Switzerland) · 2025Article
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Authors and funding
8 authors.
Funding
Abstract
The cleanliness of lubricating oil plays a key role in determining the operational health of mechanical systems, serving as a critical metric that delineates the extent of equipment wear. In this study, we present a magnetic-core-type planar coil particle detection sensor. The detection accuracy and detection limit are improved by optimizing the magnetic field inside the sensor. The optimization of the magnetic field is achieved through the finite element simulation analysis of the coil and the magnetic core. First, the finite element simulation software COMSOL 6.0 is used to model the sensor in three dimensions (3D). Then, we study the distribution of the magnetic field under different coil radii, core conductivity levels, and other parameters. We obtain the sensor structure after optimizing the magnetic field. The sensor is made using experimental methods, and the iron particles and copper particles are detected. The results show that the lower limit of detection of iron particles can reach 46 μm, and the lower limit of detection of copper particles can reach 110 μm.
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