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Data-Efficient Synchronous Machine Winding Short Circuit Faults Diagnosis Based on Frequency Response Analysis and Active Learning

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IEEE Sensors Journal 2025年第11期25卷 19804-19815页

作者： Chen, Yu Zhao, Zhongyong Liu, Jiangnan Wang, Wei Yao, Chenguo Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Wuhan430074 China Southwest University College of Engineering and Technology Chongqing400716 China Yibin Academy of Southwest University Sichuang64400 China Guangzhou Power Supply Bureau of Guangdong Power Grid Co. Ltd Guangzhou510620 China Chongqing University State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing400044 China

Winding short-circuit (SC) faults are a prevalent issue in synchronous machines, and the accurate and timely identification of these faults is critical for maintaining power system stability. Current methods for inspecting synchronous machine windings often rely on periodic inspections based on human expertise. Numerous studies have explored the application of deep learning (DL) models for detecting synchronous machine winding SC faults. However, these models often exhibit excessive complexity and overlook physical overhead, leading to inefficient utilization of computational power and data resources. To address these limitations, this study proposes a dual-channel deep learning (DL) model integrated with the active learning (AL) query strategy. In this study, winding SC faults are manually simulated on a 5 kVA synchronous machine, and corresponding frequency response analysis (FRA) data are recorded. Subsequently, the proposed method is validated on the test set and benchmarked against previous studies. Experimental results demonstrate that the proposed method significantly reduces the data annotation effort and accelerates model training to the order of seconds (under 5 seconds) while maintaining satisfactory accuracy (≥ 95%). Comparative experimental results further indicate that the proposed model, requiring only 1/20th of the labeled training samples used in previous studies, achieves a substantial reduction of approximately 99.8% in both model parameters and training time. © 2001-2012 IEEE.

关键词： Synchronous machinery

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DLLP: a deep learning-based layer prediction network for three-dimensional fluorescence microscopy

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Optics Express 2025年第9期33卷 20063-20081页

作者： Zhang, Runnan Li, Yifei Gong, Ying Hao, Xiang Tu, Shijie Feng, Ruili Gu, Zhenhong Wang, Wenbao Li, Zhifei Lu, Wei He, Mubin Chu, Jinghui School of Electrical and Information Engineering Tianjin University Tianjin 300072 China State Key Laboratory of Extreme Photonics and Instrumentation Centre for Optical and Electromagnetic Research College of Optical Science and Engineering International Research Center for Advanced Photonics Zhejiang University Hangzhou 310058 China Guangdong-Hong Kong-Macau Institute of CNS Regeneration (GHMICR) Jinan University Guangdong Province Guangzhou 510632 China Nuohai Life Science (Shanghai) Co. Ltd. Shanghai 201615 China Beijing Totop Technology Co. Ltd. Beijing 100043 China

High light-throughput microscopy stands as a potent tool in biological research, spanning applications from cell functional analysis to brain science. The pursuit of achieving elevated light throughput alongside rapid imaging speeds without the need for additional optical hardware has emerged as a pivotal focus in biomedical research. To address this challenge, we introduced a cutting-edge framework known as the deep learning-based layer predictor (DLLP). By integrating a convolutional neural network (CNN) with the inter-layer dynamic and morphological attention mechanism (IDMA) within a transformer architecture, DLLP employed a tomographic prediction technique capable of reducing the number of scanning layers in three-dimensional (3D) microscopy by over 70%, while maintaining light throughput and image fidelity. The DLLP framework significantly improved imaging speed and quality through two complementary strategies: robust unsupervised denoising to effectively mitigate electrical noise in the xy-plane caused by faster imaging and sparse recovery along the Z-axis to ensure high-quality 3D reconstruction without compromising spatial resolution. The DLLP framework has demonstrated consistent performance across various microscopy modalities, including stimulated emission depletion (STED) microscopy, fluorescence modulation optical sectioning tomography (FMOST) microscopy, multi-photon microscopy, and light-sheet microscopy, surpassing traditional methods and existing deep learning approaches in terms of accuracy and image quality. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Confocal microscopy Fluorescence microscopy Imaging techniques Scanning microscopy Spatial resolution Three dimensional microscopy

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Design, Test and Shimming of a 1.5 T Head-Only MRI Superconducting Magnet

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IEEE Transactions on Applied Superconductivity 2025年

作者： Song, Yunxing Cheng, Zhiwen Jiang, Xunhuang Li, Jianglan Li, Liang Wang, Qiuliang Huazhong University of Science and Technology Wuhan National High Magnetic Field Center Wuhan430074 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Technology Wuhan430074 China Chinese Academy of Sciences Institute of Electrical Engineering Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

As the core component of magnetic resonance imaging (MRI) system, superconducting magnet provides a high-intensity, stable and homogeneous magnetic field background for the system. The strength, stability, and homogeneity of the magnetic field directly affect the imaging quality of MRI. This paper presents the design, test and shimming of a 1.5 T Head-Only MRI superconducting magnet developed by the Wuhan National High Magnetic Field Center (WHMFC). The magnet consists of 7 primary coils and 2 shielding coils and is operated at an operating current of 510 A using liquid helium (LHe) bath cooling. The test has shown that the magnet reached the target field of 1.5 T directly after the first ramp-up without any quench. Under the magnetic field of 1.5 T, the magnetic field decay rate of the magnet is less than 0.02 ppm/hr. After 3 rounds of passive shimming, the magnet achieves a magnetic field inhomogeneity of 2.89 ppm over an imaging sphere within a diameter of 26 cm. The successful development of this magnet provides practical engineering validation for the lightweight technology of head-only MRI superconducting magnets. © 2002-2011 IEEE.

关键词： Superconducting magnets

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Tailoring the carbon nanofibers with Ti3C2Tx MXene as precursor to enhance the electromagnetic attenuation properties

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Materials Today Nano 2025年 30卷

作者： Chen, Pingan Hong, Sizeng Li, Xiangcheng Zhu, Yingli Chen, Fu Qiao, Mengke State Key Laboratory of Advanced Refractories Wuhan University of Science and Technology Wuhan430081 China Key Laboratory of High Temperature Electromagnetic Materials and Structure of MOE Wuhan University of Science and Technology Wuhan430081 China School of Information Science and Engineering Wuhan University of Science and Technology Wuhan430081 China

Carbon nanofibers can be widely used in the field of electromagnetic wave absorption due to corrosion resistance, low density and good chemical stability. Here, we report a strategy to achieve strong microwave absorption capability by adjusting the crystallinity of carbon nanofibers containing Al2O3 and TiO2. TiO2 with Ti3C2Tx MXene as a precursor decreases the crystallization temperature of Al2O3 from 1400 °C to 800 °C in the carbon nanofibers. The diameter distribution of carbon nanofibers is uniform, though the surface of carbon nanofibers is getting rough with Ti3C2Tx content increasing. The minimum reflection loss of carbon nanofibers is −55.78 dB at a thickness of 4.32 mm;the effective absorption bandwidth reaches 5.41 GHz (12.59–18 GHz) at a thickness of 1.67 mm, almost covering the Ku band. The excellent microwave absorption performance can be attributed to the synergistic effect of the non-crystalline carbon matrix and crystalline Al2O3/TiO2, in which the former improves impedance matching with free space, while the latter enhances the attenuation capability to the electromagnetic wave. © 2025

关键词： Impedance matching (electric)

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Deep Learning Advancements in Anomaly Detection: A Comprehensive Survey

arXiv

引用

arXiv 2025年

作者： Huang, Haoqi Wang, Ping Pei, Jianhua Wang, Jiacheng Alexanian, Shahen Niyato, Dusit Lassonde School of Engineering York University TorontoONM3J 1P3 Canada State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China School of Computer Science and Engineering Nanyang Technological University Singapore

The rapid expansion of data from diverse sources has made anomaly detection (AD) increasingly essential for identifying unexpected observations that may signal system failures, security breaches, or fraud. As datasets become more complex and high-dimensional, traditional detection methods struggle to effectively capture intricate patterns. Advances in deep learning have made AD methods more powerful and adaptable, improving their ability to handle high-dimensional and unstructured data. This survey provides a comprehensive review of over 180 recent studies, focusing on deep learning-based AD techniques. We categorize and analyze these methods into reconstruction-based and prediction-based approaches, highlighting their effectiveness in modeling complex data distributions. Additionally, we explore the integration of traditional and deep learning methods, highlighting how hybrid approaches combine the interpretability of traditional techniques with the flexibility of deep learning to enhance detection accuracy and model transparency. Finally, we identify open issues and propose future research directions to advance the field of AD. This review bridges gaps in existing literature and serves as a valuable resource for researchers and practitioners seeking to enhance AD techniques using deep learning. Copyright © 2025, The Authors. All rights reserved.

关键词： Deep reinforcement learning

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Impact of dielectric barrier discharge cold plasma on Dendrobium officinale polysaccharides: Physicochemical and functional properties

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International Journal of Biological Macromolecules 2025年 311卷 143740页

作者： Yu, Wujin Chen, Peng Xu, Xinhui Nie, Lanlan Huang, Zhenyu Muhammad, Ahsan Hafiz Wang, Yan Bu, Tingting Sun, Peilong Cai, Ming Department of Food Science and Technology Zhejiang University of Technology Hangzhou Zhejiang310014 China China National Light Industry China State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China State Key Laboratory in Quality Research of Chinese Medicine Institute of Chinese Medical Sciences University of Macau 999078 China

Dendrobium officinale has garnered significant attention due to its notable bioactivity and health benefits. The polysaccharide extracted from Dendrobium officinale (DOP) is the primary source of its functionality. However, its poor solubility and high viscosity necessitate the modification of its physicochemical properties. This study aimed to investigate the impact of cold plasma treatment on the physicochemical and functional properties of DOP. The results indicated that cold plasma treatment substantially increased the solubility of DOP from 87.5 % to 96.30 % and enhanced its hydrophilicity with a lower water contact angle, primarily attributed to the etching effect of plasma. Furthermore, the study confirmed the co-occurrence of cross-linking and depolymerization during the plasma discharge process. The plasma treatment reduced the viscosity of the polysaccharide solution by 10 folds and increased its thermal stability. The microstructure of the polysaccharide, examined by SEM and AFM, revealed that plasma treatment disrupted the cross-linking structure, leading to smooth agglomeration at high intensity. Moreover, the antioxidant capacity and immunoreactivity of plasma-treated DOP have been improved, and the free radical scavenging rate of the plasma-treated could reach 34.40 % at a concentration of 1 mg/mL, stimulating the secretion of cytokines TNF-α (increased 20.70 %), IL-1β (increased 26.94 %), IL-6 (increased 25.32 %), and IL-10 (increased 13.03 %) in in vitro cell tests. Accordingly, cold plasma treatment could be a novel approach to modifying polysaccharides and improving their potential applications in food and pharmaceutical sectors. © 2025

关键词： Plasma deposition

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Traceability Method of Measuring System for Arbitrary High-Voltage and High-Current Impulses

引用

IEEE Sensors Journal 2025年

作者： Yang, Ning Liu, Yi Lin, Mingxing Li, Liuxia Lin, Fuchang Long, Zhaozhi Diao, Yinglong Li, Wenting Fan, Jiawei Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Wuhan430074 China Huazhong University of Science and Technology Key Laboratory of Pulse Power Technology Ministry of Education School of Electrical and Electronic Engineering Wuhan430074 China State Grid Sichuan Electric Power Company Chengdu610041 China China Electric Power Research Institute 430072 China

High-voltage and high-current impulse waveforms, characterized by a diverse frequency spectrum, pose challenges for accurate traceability to national standards. Traditional methods for tracing impulse quantities to a single-frequency measurement standard are not universally applicable. This paper introduces a novel approach that establishes a general traceability method by mapping the impulse scale factor to a multi-frequency AC scale factor based on the energy spectrum, enabling indirect traceability to the power frequency standard under high-voltage or high-current conditions. A full-waveform inversion method is employed that integrates the frequency spectrum of measured impulse waveforms using fast Fourier transform (FFT) with the frequency response characteristics of the measuring system, which are determined through convolution based on square wave responses. This approach facilitates traceability of time parameters for arbitrary impulse waveforms. Experimental results demonstrate that the resistive impulse voltage divider's scale factor uncertainties at low and high voltages are 3.100×10-4 and 1.344×10-3, respectively. Additionally, the uncertainties for the T1 and T2 parameters of the inverted waveform of the attenuator are within 0.45% and 0.03%, respectively. These findings validate the effectiveness of our traceability theory. © 2001-2012 IEEE.

关键词： Electric frequency measurement

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Design of the high voltage isolation transmission module with low delay for ECRH system on J-TEXT

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Plasma Science and technology 2018年第2期20卷 19-25页

作者：马海燕夏冬辉王之江崔芳泰余振雄金易坤刘昌海 State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology

As a flexible auxiliary heating method,the electron cyclotron resonance heating（ECRH） has been widely used in many tokamaks and also will be applied for the J-TEXT *** meet requirements of protection and fault analysis for the ECRH system on J-TEXT,signals of gyrotrons such as the cathode voltage and current,the anode voltage and current,etc should be transmitted to the control and data acquisition *** the high voltage environment of gyrotrons,isolation transmission module based on FPGA and optical fiber communication has been designed and *** test results indicate that the designed module has strong anti-noise ability,low error rate and high transmission *** delay of the module is no more than 5 μs which can fulfill the requirements.

关键词： J-TEXT tokamak electron cyclotron resonance heating high-voltage isolation

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Equilibrium Reconstruction and Integration of EFIT with Diagnoses in J-TEXT Tokamak

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Plasma Science and technology 2016年第12期18卷 1225-1230页

作者：高海龙徐涛张帆简翔张晓卿杨州军高丽江中和庄革 State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology

The EFIT program is integrated with the high resolution laser polarimeter interferometer system（POLARIS）, the soft X-ray imaging diagnostic system（SXR） and the electron cyclotron emission radiometer（ECE） in the J-TEXT tokamak. Then some internal information about Faraday angle and the position of safety factor q=1 can be obtained as a constraint to EFIT. The modified EFIT code is used to calculate the internal parameters such as flux function, safety factor q, pressure and current density.

关键词： EFIT equilibrium reconstruction diagnoses

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Mode-Coupling Analysis of Parametric Decay Instability in Magnetized Plasmas

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Plasma Science and technology 2014年第9期16卷 809-814页

作者：袁媛江中和郭伟欣孙新锋胡希伟 State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology

In this paper, derived from Maxwell and fluid equations of plasmas, unified nonlinear wave equations are used to describe the parametric decay instability （PDI） in magnetized plasmas, and in view of mode-coupling, we can obtain all the possible PDI channels. By solving the nonlinear equations with a mode-coupling method, we obtain the growth rate of the PDI, of which all of the three waves are ordinary mode （O-mode） or extraordinary mode （X-mode） wave. Under the dipole approximation, an explicit formula of the growth rate of the X-mode and the condition of the equilibrium density scale are obtained. According to the existence conditions of three X-mode waves, this kind of instability might exist in ECRH with the second harmonic X-mode wave.

关键词： magnetized plasma parametric decay instability mode-coupling theory,growth rate

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