IEEE Transactions on Magnetics最新文献_第3页

Artificial Learning Algorithms for Partial Discharge Classification 局部放电分类的人工学习算法

IF 1.9 3区工程技术

IEEE Transactions on Magnetics Pub Date : 2026-07-01 Epub Date: 2025-12-09 DOI: 10.1109/TMAG.2025.3641965

Silvia Licciardi;Alessio Di Fatta;Guido Ala;Pietro Romano;Antonino Imburgia;Elisa Francomano

{"title":"Artificial Learning Algorithms for Partial Discharge Classification","authors":"Silvia Licciardi;Alessio Di Fatta;Guido Ala;Pietro Romano;Antonino Imburgia;Elisa Francomano","doi":"10.1109/TMAG.2025.3641965","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3641965","url":null,"abstract":"Partial discharges (PDs) are localized dielectric breakdowns that may occur within insulating systems under high electric stress, without leading to total failure. Even if, in alternating current (ac) systems, the PD recognition is a fully explored field, accurate identification of PD types under direct current (dc) conditions remains an open problem due to the complexity and variability of the discharge phenomena. In this study, a data-driven classification framework is proposed, employing artificial learning (AL) techniques to distinguish experimentally acquired PD signals corresponding to three typical defect types. The approach compares conventional machine learning (ML) models—such as decision trees (DTs) and discriminant analysis (DA)—with a deep neural architecture based on long short-term memory (LSTM) networks capable of capturing temporal patterns and nonlinear dynamics in PD waveforms. All models were trained and tested on a large dataset of experimental measurements, with hyperparameter optimization used to enhance classification accuracy while preserving computational efficiency. The experimental results demonstrate the potential of AL-based methods also for reliable PD recognition in dc, opening perspectives for condition monitoring, failure prevention, and intelligent diagnostics in high-voltage insulation systems.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"62 7","pages":"7204006-7204006"},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148512939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A New Anhysteresis Curve for Magnetic Materials 磁性材料的一种新的无磁滞曲线

IF 1.9 3区工程技术

IEEE Transactions on Magnetics Pub Date : 2026-07-01 Epub Date: 2025-12-01 DOI: 10.1109/TMAG.2025.3639094

Alexander Sauseng;Klaus Roppert;Manfred Kaltenbacher

引用次数: 0

A Semi-Analytical Method for the Analysis of Electrical Machines With Complex 3-D Salient Geometries 复杂三维凸形电机的半解析分析方法

IF 1.9 3区工程技术

IEEE Transactions on Magnetics Pub Date : 2026-07-01 Epub Date: 2025-09-25 DOI: 10.1109/TMAG.2025.3614345

M. Ramos Friedmann;D. Ceylan;M. Merdzan;E. A. Lomonova

引用次数: 0

Accurate Retrieval of Effective Magnetic Permeability in WPT Systems Using Circuit Modeling of Resonant Metasurfaces 利用谐振超表面电路建模精确检索WPT系统的有效磁导率

IF 1.9 3区工程技术

IEEE Transactions on Magnetics Pub Date : 2026-07-01 Epub Date: 2025-10-13 DOI: 10.1109/TMAG.2025.3621129

F. M. Freitas;A. Bréard;L. Pace;S. T. M. Gonçalves;I. V. Soares;U. C. Resende;C. Vollaire

{"title":"Accurate Retrieval of Effective Magnetic Permeability in WPT Systems Using Circuit Modeling of Resonant Metasurfaces","authors":"F. M. Freitas;A. Bréard;L. Pace;S. T. M. Gonçalves;I. V. Soares;U. C. Resende;C. Vollaire","doi":"10.1109/TMAG.2025.3621129","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3621129","url":null,"abstract":"This article presents a fast and accurate method for extracting the effective magnetic permeability in wireless power transfer (WPT) systems operating with resonant metamaterials (MMTs). The approach combines a circuit model (CM) to compute current distribution and the Biot–Savart law to evaluate the magnetic field in 3-D space, enabling permeability retrieval without relying on complex unit-cell characterization. Two setups are validated: one with a single MMT cell and another with a magnetic metasurface (MMTS) inserted between transmitter (Tx) and receiver (Rx) coils. Measurements and simulations at industrial, scientific, and medical (ISM) frequencies 27.12 and 40.68 MHz show strong consistency in both magnetic response and power transfer efficiency (PTE). The proposed method captures resonant behavior and spatial variation of the magnetic field while maintaining low computational cost. Compared with full-wave simulations, the CM achieves a speedup of over 1000×, enabling the rapid evaluation of spatial configurations and permeability profiles. This capability supports efficient system design and opens paths toward metasurface optimization in near-field WPT applications.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"62 7","pages":"7000606-7000606"},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148513792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Physics-Informed Neural Networks With Learning Rate Annealing and Domain-Decomposition Subnetworks for Solving 3-D Maxwell’s Equations 基于学习率退火和区域分解子网络的物理信息神经网络求解三维Maxwell方程组

IF 1.9 3区工程技术

IEEE Transactions on Magnetics Pub Date : 2026-07-01 Epub Date: 2026-03-08 DOI: 10.1109/TMAG.2026.3691331

Haoran Qin;Tiancheng Zhang;Peili Ping;Huaguang Bao;Aiqaing Cheng;Zongguang Yu;Dazhi Ding

{"title":"Physics-Informed Neural Networks With Learning Rate Annealing and Domain-Decomposition Subnetworks for Solving 3-D Maxwell’s Equations","authors":"Haoran Qin;Tiancheng Zhang;Peili Ping;Huaguang Bao;Aiqaing Cheng;Zongguang Yu;Dazhi Ding","doi":"10.1109/TMAG.2026.3691331","DOIUrl":"https://doi.org/10.1109/TMAG.2026.3691331","url":null,"abstract":"In this work, a novel approach based on physics-informed neural networks (PINNs) has been proposed for solving 3-D Maxwell’s equations. The proposed method employs a modified fully connected neural architecture integrated with transformer networks, which significantly enhances the capacity in minimizing approximation errors. A learning rate annealing strategy is adopted to dynamically adjust the penalty weights based on loss gradients, thereby balancing multiple objective terms and improving prediction accuracy. To handle multi-material domains, dedicated subnetworks are used along with enforced boundary conditions to ensure field continuity at interfaces. The accuracy and robustness of the proposed framework are validated through simulations of resonant cavities and waveguides, showing excellent agreement between predicted and analytical field solutions. The results show that the proposed approach reduces prediction errors compared to vanilla PINNs while maintaining stable convergence behavior. These results demonstrate the effectiveness of the method for solving 3-D electromagnetic problems within Cartesian coordinates. The method uses linear dielectric materials and boundaries aligned with the coordinate axes. The framework provides a foundation for future extensions to arbitrary boundaries, multi-scale geometries, and nonlinear dielectric materials, thereby broadening its applicability in practical engineering design and analysis.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"62 7","pages":"7204810-7204810"},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148513964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Magnetics Society Information IEEE磁学学会信息

IF 1.9 3区工程技术

IEEE Transactions on Magnetics Pub Date : 2026-07-01 Epub Date: 2026-07-13 DOI: 10.1109/TMAG.2026.3707987

引用次数: 0

Computational Investigation of Magnetophoretic Separation of Blood-Cell-Inspired Particles in Serpentine Microchannels 蛇形微通道中造血微粒磁泳分离的计算研究

IF 1.9 3区工程技术

IEEE Transactions on Magnetics Pub Date : 2026-07-01 Epub Date: 2026-03-21 DOI: 10.1109/TMAG.2026.3695600

Sumit Kumar Mehta;Prabal Baishya;Khushi Pathak;Jinmay Kalita;Somchai Wongwises;Pranab Kumar Mondal

{"title":"Computational Investigation of Magnetophoretic Separation of Blood-Cell-Inspired Particles in Serpentine Microchannels","authors":"Sumit Kumar Mehta;Prabal Baishya;Khushi Pathak;Jinmay Kalita;Somchai Wongwises;Pranab Kumar Mondal","doi":"10.1109/TMAG.2026.3695600","DOIUrl":"https://doi.org/10.1109/TMAG.2026.3695600","url":null,"abstract":"We computationally investigate magnetophoretic separation characteristics of blood-cell-inspired particles representing white blood cells (WBCs) and red blood cells (RBCs) in serpentine microchannels under saline-water diluted conditions. The flow field inside the microchannel and the induced magnetic field distribution are numerically simulated using a finite-element-based framework, while particle trajectories are obtained through Newtonian particle tracking. The study systematically examines the influence of magnetic configuration, channel geometry, and flow conditions on magnetic field gradients, particle trajectories, recovery, purity, and separation efficiency. The results demonstrate that serpentine microchannels generate stronger and more non-uniform magnetic field gradients compared to planar configurations, thereby enhancing magnetophoretic manipulation and particle separation. The influence of magnet geometry is also analyzed, revealing that square-shaped magnets provide the most favorable separation characteristics among the investigated configurations due to stronger localized magnetic field gradients. Furthermore, the combined effects of Reynolds number, serpentine channel amplitude, and magnet position are shown to govern the balance between magnetophoretic and hydrodynamic drag forces, leading to distinct operating windows for enhanced separation performance. The present work should be interpreted as a first-order computational design study employing simplified particle surrogates under low-Reynolds-number conditions. The findings provide physical insights and computational design guidelines for the development and optimization of magnetophoretic microfluidic separators for blood-cell-inspired particles in lab-on-chip applications.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"62 7","pages":"6600122-6600122"},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148514083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Toward Simplifying Electrical Machine Design With Automated CAD Component Identification Using Mask R-CNN 基于掩模R-CNN的自动化CAD元件识别简化电机设计

IF 1.9 3区工程技术

IEEE Transactions on Magnetics Pub Date : 2026-07-01 Epub Date: 2026-02-06 DOI: 10.1109/TMAG.2026.3662284

Abidur Rahman;David Lowther

{"title":"Toward Simplifying Electrical Machine Design With Automated CAD Component Identification Using Mask R-CNN","authors":"Abidur Rahman;David Lowther","doi":"10.1109/TMAG.2026.3662284","DOIUrl":"https://doi.org/10.1109/TMAG.2026.3662284","url":null,"abstract":"The state-of-the-art design processes for electrical machines (eMachine) are template-based methods and design-from-scratch approaches. Over the past four decades, significant advancements have been made to make these methods effective in terms of electromagnetic performance. However, the state of the art cannot provide information on the topology and the components of an eMachine from a given non-parametrized computer-aided design (CAD). This information is imperative for the automatic selection of an appropriate simulation profile to meet the required key performance indicators (KPIs), enhancing the numerical computation of electromagnetic fields, and improving the user experience through an improved user interface. Moreover, it can be used to generate a parametric version of a given CAD design, which can subsequently be utilized by an optimization tool for geometric refinement and optimal material selection. The first step to achieve this is recognizing the components and their relative special positioning. This article uses a Mask Region-based Convolutional Neural Network (Mask R-CNN), an object detection technique, to identify the components of an eMachine from a CAD design.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"62 7","pages":"7204606-7204606"},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148514752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design of WFSM Using Sizing Method Combining 2-D Equivalent Magnetic Circuit Considering Nonlinear Characteristics 考虑非线性特性的二维等效磁路结合定尺法设计WFSM

IF 1.9 3区工程技术

IEEE Transactions on Magnetics Pub Date : 2026-07-01 Epub Date: 2025-10-23 DOI: 10.1109/TMAG.2025.3624623

Kyoung-Soo Cha;Soo-Hwan Park;Young-Hoon Jung

{"title":"Design of WFSM Using Sizing Method Combining 2-D Equivalent Magnetic Circuit Considering Nonlinear Characteristics","authors":"Kyoung-Soo Cha;Soo-Hwan Park;Young-Hoon Jung","doi":"10.1109/TMAG.2025.3624623","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3624623","url":null,"abstract":"This article proposes a novel sizing method of wound field synchronous motor (WFSM) using a 2-D equivalent magnetic circuit (2-D EMC) considering nonlinear characteristics. The conventional sizing method is an analytical method predicting motor performance using a proportional formula based on size-related variables of the motor, which are shape ratio (SR), torque per rotor volume (TRV), and torque density (TD). However, the accurate results cannot be obtained only from the proportional formula because the performance of the motor varies greatly depending on the magnetic saturation of the core. In particular, since the WFSM does not use a permanent magnet (PM) for the field, it is important to reflect the magnetic saturation of the field core. Therefore, in this article, a novel sizing method of WFSM based on the 2-D EMC, which is a numerical method used to fast and accurately calculate the performance of the motor considering the magnetic saturation of the core, is proposed. Using the proposed design method, it is possible to not only accurately predict the motor characteristics according to the size but also determine the motor size that satisfies the requirement performances. The validity of the proposed sizing process is verified through simulations and experiments.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"62 7","pages":"7400906-7400906"},"PeriodicalIF":1.9,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148516410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Electromagnetic Field Analysis on High-Frequency Response of Inductor Considering Frequency Dependence of Magnetic Permeability 考虑磁导率频率依赖性的电感器高频响应电磁场分析

IF 1.9 3区工程技术

IEEE Transactions on Magnetics Pub Date : 2026-07-01 Epub Date: 2025-09-23 DOI: 10.1109/TMAG.2025.3613581

Xuanda Hou;Hiroshi Dozono;Kazuhiro Muramatsu;Keisuke Fujisaki;Nguyen Gia Minh Thao;Yanhui Gao;Weimin Guan;Jiaxin Yuan

引用次数: 0