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Ionization waves in nanosecond pulsed atmospheric pressure plasma jets in argon

High Voltage 2021年第4期6卷 665-673页

作者： Bangdou Huang Cheng Zhang Wenchao Zhu Xinpei Lu Tao Shao Beijing International S&T Cooperation Base for Plasma Science and Energy Conversion Institute of Electrical EngineeringChinese Academy of SciencesBeijingChina University of Chinese Academy of Sciences BeijingChina State Key Laboratory of NBC Protection for Civilian BeijingPeople’s Republic of China State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and TechnologyWuhanHubeiChina

Typical ionization waves(IWs)are observed during the propagation of nanosecond pulsed atmospheric pressure plasma jets(APPJs)with argon flow,combining both the measurement of the axial electric field(Ez)and the temporal resolved optical *** movement of the luminous APPJ head is recognized as the development of the IW front,accompanied with the propagation of the peak electric ***,the radial distribution of Ez transits from a central peak profile before the IW front arrives to a hollow profile after the pass of the IW *** for the temporal Ez trend,there is a mode transition from the single-peak feature under a low peak voltage to the double-peak feature under a higher peak voltage,indicating the existence of both primary and secondary *** effect of target conditions on the IWs in APPJs is also *** a metal target,no residual electric field is observed before imposing the high-voltage ***,with a dielectric target,the residual surface charges generate a back-ground electric field in the opposite direction to that during IW *** the free APPJ(with no target),on the voltage falling edge,a negative electric field drives the electron flow to compensate the positive ions left over during the forward IW propa-gation on the voltage rising edge.

关键词： field luminous dielectric

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Mechanical-electromagnetic Coupling Simulation of Microwave Tubes Based on Dynamic Mesh technology

Mechanical-Electromagnetic Coupling Simulation of Microwave ...

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International Conference on Vacuum Electronics

作者： Junhui Yin Longwei Deng Xinyu Cao Qing He Chaoyang Zhang Li Xu Xing Li Bin Li National Key Laboratory of Science and Technology on Vacuum Electronics Key Laboratory of Large-Scale Electromagnetic Industrial Software Ministry of Education School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen China

ISBN: (数字)9798350348705

ISBN: (纸本)9798350348712

Small mechanical perturbations can potentially alter the electromagnetic properties of microwave tubes. It is imperative to consider the impact of displacement deformation on these properties, as it can alter the electromagnetic boundary conditions and the location of the medium computational domain. The structure displacement deformation is crucial to the performance analysis of microwave tubes. This paper introduces a multi-physics simulator system, which is developed using an integrated framework and facilitates mechanical-electromagnetic coupling simulation. Utilizing dynamic mesh technology, the finite element model of the mechanical and electromagnetic computational domains can be automatically updated. Consequently, the electromagnetic computational domain can reflect displacement deformation post-mechanical analysis, eliminating the need for designer intervention. Numerical results indicate that the technology proposed herein can perform mechanical-electromagnetic coupling analysis and accurately depict the actual physical characteristics.

关键词： Couplings Deformable models Microwave technology Analytical models Deformation Computational modeling Perturbation methods Performance analysis Vacuum electronics electromagnetics

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PDCapsNet: A Convolution Neural Network Method for COVID-19 Detection from Chest X-Ray Images 13

PDCapsNet: A Convolution Neural Network Method for COVID-19 ...

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13th International Conference on Information technology in Medicine and Education, ITME 2023

作者： Liang, Zhihao Lu, Huijuan You, Cunqian Zhu, Wenjie Xie, Li Yao, Yudong College of Information Engineering China Jiliang University Key Laboratory of Electromagnetic Wave Information Technology and Metrology Zhejiang Province Hangzhou China College of Information Engineering China Jiliang University Drore Information and Technology Co. LTD. Zhejiang Province Hangzhou China College of Information Engineering China Jiliang University Modern Educational Technology Center Zhejiang Province Hangzhou City China College of Biomedical Engineering and Instrumentation Science Zhejiang University Institute of Advanced Digital Technologies and Instrumentation Zhejiang Province Hangzhou China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ United States

ISBN: (纸本)9798350319156

The COVID-19 epidemic started in 2019 and it is still important to develop intelligent and efficient diagnostic methods for the detection of COVID-19. In the task of COVID-19 X-ray image recognition, conventional deep neural networks encounter challenges in effectively discerning distinctive features within pneumonia images, resulting in limited generalization capability when confronted with novel samples. To address this issue, we introduce a novel model in this paper, denoted as PDCapsNet. The model effectively exploits Pyconv's multi-scale fusion technique and leverages the capsule network's capacity to encapsulate diverse attributes of specific entities within COVID-19 X-ray images, resulting in enhancements in both accuracy and generalization. Experimental results show that the proposed model outperforms other previous related works. © 2023 IEEE.

关键词： COVID-19

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Adaptive Anomaly Detection Disruption Prediction Starting from First Discharge on Tokamak

arXiv

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arXiv 2024年

作者： Ai, X.K. Zheng, W. Zhang, M. Ding, Y.H. Chen, D.L. Chen, Z.Y. Guo, B.H. Shen, C.S. Wang, N.C. Yang, Z.J. Chen, Z.P. Pan, Y. Shen, B. Xiao, B.J. State Key Laboratory of Advanced Electromagnetic Technology International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China Institute of Plasma Physics Chinese Academy of Sciences Hefei230031 China

Plasma disruption presents a significant challenge in tokamak fusion, especially in large-size devices like ITER, where it can cause severe damage and economic losses. Current disruption predictors mainly rely on data-driven methods, requiring extensive discharge data for training. However, future tokamaks require disruption prediction from the first shot, posing challenges of data scarcity and difficulty in training and hyperparameter selection during the early operation period. In this period disruption prediction also aims to support safe exploration of operation range and accumulate necessary data to develop advanced prediction models. Thus, predictors must adapt to evolving plasma environments during this exploration phase. To address these challenges, this study proposes a cross-tokamak adaptive deployment method based on the Enhanced Convolutional Autoencoder Anomaly Detection (E-CAAD) predictor. This method enables disruption prediction from the first discharge of new devices, addressing the challenges of cross-tokamak deployment of data-driven disruption predictors. Experimental results demonstrate the ability of the E-CAAD model trained on existing devices to effectively differentiate between disruption precursors and non-disruption samples on new devices, proving the feasibility of model cross-device transfer. Building upon this, adaptive learning from scratch and threshold adaptive adjustment strategies are proposed to achieve model cross-device transfer. The adaptive learning from scratch strategy enables the predictor to fully use scarce data during the early operation of the new device while rapidly adapting to changes in the operation environment. The warning threshold adaptive adjustment strategy addresses the challenge of selecting warning thresholds on new devices where the validation set is lacking, ensuring that the warning thresholds adapt to changes in the operation environment. Finally, experiments transferring the model from J-TEXT to EAST e

关键词： Anomaly detection

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Velocity Disturbance Rejection Control of High-Speed Linear Induction Motor Based on Rolling Prediction Matrix

Velocity Disturbance Rejection Control of High-Speed Linear ...

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International Conference on Power Electronics and Motion Control (IPEMC)

作者： Xinyu Jiang Fei Xu Zixin Li Liming Shi Yaohua Li Key Laboratory of Power Electronics and Electric Drive Institute of Electrical Engineering Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Institute of Electrical Engineering and Advanced Electromagnetic Drive Technology Qilu Zhongke Jinan China

ISBN: (数字)9798350351330

ISBN: (纸本)9798350351347

Uncertainty disturbance of measured velocity can cause thrust instability, impeding the transonic process of high-speed linear induction motors (HS-LIM). To tackle this issue, a Velocity Disturbance Rejection Control (VDRC) method based on the Rolling Prediction Matrix (RPM) is proposed in this paper. The method employs multi-point speed predictions to identify uncertain disturbances and produce a virtual speed to substitute the affected sensor speed. Simulation results validate that the proposed technique successfully achieves stable transonic acceleration for HS-LIM.

关键词： Induction motors Uncertainty Simulation Measurement uncertainty Asia Control systems Matrices

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A Na-Li dual cation liquid metal battery with high electrode utilization and high cycling stability

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Energy Storage Materials 2024年 73卷

作者： Feng, Shaoming Fan, Lei Zhou, Hao Li, Haomiao Yan, Shuai Zhang, Weixin Guo, Yewei Li, Bo Jiang, Kai Wang, Kangli School of Materials Science and Engineering Huazhong University of Science and Technology Hubei Wuhan430074 China State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Hubei Wuhan430074 China Institute of Electric Power Science of Guizhou Power Grid Co. Ltd Guizhou Guiyang550000 China

Liquid metal batteries (LMBs) with Na anode exhibit the advantages of low-cost, high-safety, long-lifespan, and easy scale-up, making them promising for large-scale energy storage applications. However, the high solubility of Na and its sluggish kinetics in discharge products result in severe self-discharge and low cathode utilization, significantly hindering the development of Na-based LMBs. In this study, a stable Na-Li dual cation LMB with metal Sb cathode is designed based on the in-situ displacement reaction between Na and molten salts of lithium halides electrolyte. This design effectively suppresses the self-discharge of the battery, and the multistage discharge mechanism of the dual-cation system enhances cathode utilization. Moreover, the self-healing property of the Sb cathode protects the electrode against volume expansion and degradation, enhancing cycling performance. The Na-Li| LiCl-KCl-NaCl |Sb cell was constructed and operated at 485 °C. The battery retained 97.02 % of its capacity after 800 cycles at 0.6 C, with a decay rate of 0.00373 % per cycle. Furthermore, the battery achieves a cathode material utilization of 89 % at 0.6 C. These improvements effectively promote the development and application of LMBs. © 2024

关键词： Sodium chloride

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The engineering Practical Calculation Method of Circulating Current in YD-connected Transformer 2

The Engineering Practical Calculation Method of Circulating ...

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2nd IEEE China International Youth Conference on Electrical engineering, CIYCEE 2021

作者： Cao, Wenbin Qi, Xuanwei Wang, Song Chen, Ming Yin, Xianggen Wen, Minghao State Grid Zhejiang Electrical Power Research Institute Hangzhou310014 China Huazhong University of Science and Technology Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Wuhan430074 China

ISBN: (纸本)9781665400640

The circulating current in the D-winding may cause primary current waveform distortion, and the reliability of the restraint criterion based on the typical magnetizing inrush current characteristics will be affected. The magnetizing inrush current with typical characteristics is the sum of primary current and circulating current. Using the circulating current to compensate the primary current can improve the reliability of the differential protection. When the phase is not saturated, the magnetizing inrush current is about zero. Therefore, the primary current of unsaturated phase can be replaced by the opposite of the circulating current. Based on this, an engineering practical calculation method for circulating current is proposed. In the method, the segmented primary currents are used to replace the circulating current. Phasor analysis is used to demonstrate the application effect of this method when remanence coefficients are different. The method is simple and practical, and has strong applicability and high reliability. Simulation and recorded waveforms have verified the effectiveness of the method. © 2021 IEEE.

关键词： Reliability

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Enhanced Simulation Study of ITER Core X-Ray Crystal Spectroscopy 51

Enhanced Simulation Study of ITER Core X-Ray Crystal Spectro...

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51st IEEE International Conference on Plasma Science, ICOPS 2024 and 4th Asia-Pacific Conference on Plasma and Terahertz Science, APCOPTS 2024

作者： Jin, X. Cheng, Z. Zhang, J. Yan, W. Chen, Z. Pablant, N. Gao, L. Lu, D. O’Mullane, M. Tieulent, R. Barnsley, R. State Key Laboratory of Advanced Electromagnetic Technology International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China ITER Organization Route de Vinon-sur-Verdon CS 90 046 Saint-Paul-lez-DuranceCedex 13067 France Princeton Plasma Physics Laboratory PrincetonNJ08540 United States Institute of Plasma Physics HFIPS Chinese Academy of Science Hefei230031 China Department of Physics SUPA University of Strathclyde GlasgowG4 ONG United Kingdom

ISBN: (纸本)9798350360912

The core X-Ray Crystal Spectroscopy (XRCS-Core) is a critical diagnostic tool dedicated to providing ion temperature and plasma rotation for the International Tokamak Experimental Reactor (ITER). To meet space constraints, a novel dual-reflection configuration involving multiple flat reflectors and spherical curved crystals has been proposed for ITER XRCS-Core [1]. © 2024 IEEE.

关键词： Tokamak devices

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Deep Learning Advancements in Anomaly Detection: A Comprehensive Survey

arXiv

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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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Design and control of the accelerator grid power supply-conversion system applied to CFETR N-NBI prototype

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Plasma Science and technology 2020年第8期22卷 175-183页

作者： Dongyu WANG Ming ZHANG Shaoxiang MA Shu YANG Kexun YU Yuan PAN State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and TechnologyWuhan 430074People's Republic of China School of Electrical and Electronic Engineering Huazhong University of Science and TechnologyWuhan 430074People's Republic of China

The acceleration grid power supply(AGPS)rated 200 kV/25 A is a key component devoted to supply the acceleration grids of the China fusion engineering test reactor negative-ion-based neutral beam injector(N-NBI)prototype *** paper focused on the design and control of the AGPS conversion system(AGPS-CS),with emphasis on the requirement of the wide range output voltage and rise time.A voltage regulation switch at the front of step-down transformer is applied to optimize the grid current and DC-link ***,a new feedforward control strategy with piecewise PI compensator is proposed to improve the characteristics of *** simulation results of the proposed AGPS-CS are presented,proving the performance of the power supply to achieve the desired requirements.

关键词： CFETR NBI accelerator grid power supply feedforward control high voltage power supply

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