Deep Neural Network-Based Design of Planar Coils for Proximity Sensing Applications

محفوظ في:
التفاصيل البيبلوغرافية
الحاوية / القاعدة:Sensors vol. 25, no. 14 (2025), p. 4429-4453
المؤلف الرئيسي: Lalla Abderraouf
مؤلفون آخرون: Di Barba Paolo, Hausman Sławomir, Mognaschi Maria Evelina
منشور في:
MDPI AG
الموضوعات:
الوصول للمادة أونلاين:Citation/Abstract
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الوصف
مستخلص:This study develops a deep learning procedure able to identify a planar coil geometry, given the desired magnetic field map. This approach demonstrates its capability to discover suitable coil designs that produce desired field characteristics with high accuracy and efficiency. The generated coils show strong agreement with target magnetic fields, enabling manufacturers to achieve simpler structures and improved performance. This method is suitable for inductive proximity sensors, wireless power transfer systems, and electromagnetic compatibility applications, offering a powerful and flexible tool for advanced planar coil design.
تدمد:1424-8220
DOI:10.3390/s25144429
المصدر:Health & Medical Collection