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The propagation of Quasi-static region during granular impact

Particuology 2023年第12期83卷 1-7页

作者： Moyu Yang Ran Li Yingnan Xiu Qiang Zeng Xiaoyan Ye Hui Yang School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai200093China Center for Particle-Laden Turbulence Key Laboratory of Mechanics on Disaster and Environment in Western China attached to the Ministry of Education of ChinaDepartment of Mechanics and Engineering ScienceSchool of Civil Engineering and MechanicsLanzhou UniversityLanzhou730000China

In this paper,through experiments and DEM simulations,it is found that there is a ring-shaped region named Quasi-static Region between the particles expanding outward and the particles collapsing inward during the impact ***-static Region is always generated from the impact point at the same time,and then spreads out at a uniform *** the propagation of Quasi-static Region,the velocity of the particles in the particle extend region varies linearly in space and *** the change rate is only related to the properties of the particle *** simulation results show that the particle flow in Quasi-static Region is elastic-inertial flow,while the particle flow expanding outward and collapsing inward is inertial flow.

关键词： Impact Quasi-staticregion Propagation Shearflow

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Transformer Health Monitoring via Synchrophasors

Transformer Health Monitoring via Synchrophasors

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2023 IEEE International Conference on Environment and electrical engineering and 2023 IEEE Industrial and Commercial Power systems Europe, EEEIC / I and CPS Europe 2023

作者： Paramo, Gian Bretas, Arturo University of Florida Electrical and Computer Engineering GainesvilleFL United States Distributed Systems Group Pacifc Northwest National Laboratory RichlandWA United States

ISBN: (纸本)9798350347432

Traditional transformer protection schemes such as differential protection operate once the transformer is in a critical state. Proactive means of transformer health evaluation such as Sweep Frequency Response Analysis, can only be performed periodically with the transformer out-of-service. This work presents a framework where the health and structural integrity of transformers is monitored via synchrophasors in real-time. Synchrophasors and subspace estimation techniques are used to build reduced-order models which are then analyzed across multiple domains. A diagnostics algorithm is developed and tested via Matlab simulations. Test results are promising, opening up new prospects in transformer protection research. © 2023 IEEE.

关键词： MATLAB

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electrically tunable planar liquid-crystal singlets for simultaneous spectrometry and imaging

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Light(Science & Applications) 2024年第11期13卷 2589-2598页

作者： Zhou Zhou Yiheng Zhang Yingxin Xie Tian Huang Zile Li Peng Chen Yan-qing Lu Shaohua Yu Shuang Zhang Guoxing Zheng Electronic Information School and School of MicroelectronicsWuhan UniversityWuhan 430072China NUS Graduate School National University of SingaporeSingapore 119077Singapore Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore National Laboratory of Solid State Microstructures Key Laboratory of Intelligent Optical Sensing and Manipulationand College of Engineering and Applied SciencesNanjing UniversityNanjing 210093China Peng Cheng Laboratory Shenzhen 518055China New Cornerstone Science Laboratory Department of PhysicsUniversity of Hong KongHong KongChina Department of Electrical and Electronic Engineering University of Hong KongHong KongChina Wuhan Institute of Quantum Technology Wuhan 430206China

Conventional hyperspectral cameras cascade lenses and spectrometers to acquire the spectral datacube,which forms the fundamental framework for hyperspectral ***,this cascading framework involves tradeoffs among spectral and imaging performances when the system is driven toward ***,we propose a spectral singlet lens that unifies optical imaging and computational spectrometry functions,enabling the creation of minimalist,miniaturized and high-performance hyperspectral *** a paradigm,we capitalize on planar liquid crystal optics to implement the proposed framework,with each liquid-crystal unit cell acting as both phase modulator and electrically tunable spectral *** with various targets show that the resulting millimeter-scale hyperspectral camera exhibits both high spectral fidelity(>95%)and high spatial resolutions(~1.7 times the diffraction limit).The proposed“two-in-one”framework can resolve the conflicts between spectral and imaging resolutions,which paves a practical pathway for advancing hyperspectral imaging systems toward miniaturization and portable applications.

关键词： crystal planar singlet

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Dynamic Modeling of Key Operating Parameters for Supercritical Circulating Fluidized Bed Units based on Data-Knowledge-Driven Method

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Journal of Thermal Science 2024年第3期33卷 1216-1230页

作者： YU Haoyang GAO Mingming ZHANG Hongfu CHEN Jiyu LIU Jizhen YUE Guangxi The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer EngineeringNorth China Electric Power UniversityBeijing102206China CHN Energy New Energy Technology Research Institute Co. Ltd.Beijing102209China Department of Energy and Power Engineering Tsinghua UniversityBeijing100084China

To address the pressing need for intelligent and efficient control of circulating fluidized bed(CFB)units,it is crucial to develop a dynamic model for the key operating parameters of supercritical circulating fluidized bed(SCFB)***,data-knowledge-driven dynamic model of bed temperature,load,and main steam pressure of the SCFB unit has been ***,a knowledge-driven method is employed to develop a dynamic model for key operating parameters of SCFB *** model parameters are determined based on the operating data of the unit and continuously optimized in real ***,Bidirectional Long Short-Term Memory combined with Convolutional Neural Network and Attention Mechanism is utilized to build the dynamic model of bed temperature,load,and main steam ***,a collaboration and integration method based on the critic weight method and the variation coefficient method is proposed to establish data-knowledge-driven model of key operating parameters for SCFB *** model displays great accuracy and fitting ability compared with other methods and effectively captures the dynamic characteristics,which can provide a research basis for the design of intelligent flexible control mode of SCFB unit.

关键词： circulating fluidized bed dynamic model data-knowledge-driven method deep learning power plant

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Low-Cost, High-Performance Algorithm and Hardware Architecture for SAO Mode Decision 2

Low-Cost, High-Performance Algorithm and Hardware Architectu...

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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Hou, Bingjing Liu, Chang Zhang, Yuejun Huang, Leilei Jing, Minge Fan, Yibo Fudan University State Key Laboratory of Integrated Chips and Systems Shanghai China Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China East China Normal University Institute of Microelectronic Circuits and Systems Shanghai China

ISBN: (纸本)9798331515669

Sample adaptive offset (SAO) is applied for reducing sample distortion and attenuating ringing artifacts in both HEVC and VVC standards. The rate-distortion optimization process is used to select the best SAO parameter. It accounts for the majority of SAO complexity and determines the SAO filtering performance. Therefore, the rate-distortion cost calculation should be well handled to achieve both low cost and high coding performance. In this paper, we propose a simplified and optimized rate estimation algorithm based on the characteristics of SAO parameter syntax and entropy coding process. And we propose a hierarchical flow for rate-distortion cost calculation to further reduce the computational cost and storage cost for SAO mode decision hardware. The results show that the proposed algorithm achieves an average YUV loss of -0.10%, and the proposed SAO mode decision hardware architecture can be implemented by only 21.8k gates using TSMC 65nm process under 400 MHz. © 2024 IEEE.

关键词： Electric distortion

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Enhancing single-lead electrocardiogram arrhythmia detection with empirical mode decomposition

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Neural Computing and Applications 2025年第17期37卷 11583-11605页

作者： Issa, Mohamed F. Yousry, Ahmed Tuboly, Gergely Wang, Zeyu Zoltan, Juhasz Selim, Mazen M. AbuEl-Atta, Ahmed H. Department of Scientific Computing Faculty of Computers and Artificial Intelligence Benha University Benha13511 Egypt Department of Computer Science Faculty of Computers and Artificial Intelligence Benha University Benha13511 Egypt Department of Electrical Engineering and Information Systems University of Pannonia Veszprem8200 Hungary Department of Mechatronics Delta University for Science and Technology Gamasa35712 Egypt

Cardiac arrhythmias pose a significant challenge to health care, requiring accurate and reliable detection methods to enable early diagnosis and treatment. However, traditional ECG beat classification methods often lack robustness and fail to generalize effectively to diverse clinical scenarios, particularly when using single-lead-I recordings, which are less studied compared to lead II. To address this gap, this paper proposes a novel method that combines deep learning and empirical mode decomposition (EMD) for arrhythmia detection using single-lead-I ECG recordings obtained with electrodes on each hand. The hybrid model comprises 149 layers of one-dimensional convolution, max pooling, and residual blocks. By leveraging EMD, it classifies ECG beats into normal beats, premature ventricular contractions, and atrial premature beats with high sensitivity (99.86%, 99.72%, and 99.84%, respectively) using the first four intrinsic mode functions (IMFs). The proposed method is applicable in clinical and out-of-hospital monitoring scenarios, and an accompanying web application provides real-time analysis and diagnostic results. This approach addresses a critical gap in lead-I ECG analysis, enhancing diagnostic precision and expanding the scope of ECG applications in health care. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Empirical mode decomposition

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A Holistic State Estimation Framework for Active Distribution Network with Battery Energy Storage System

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Journal of Modern Power systems and Clean Energy 2022年第3期10卷 627-636页

作者： Shaojian Song Huangjiao Wei Yuzhang Lin Cheng Wang Antonio Gómez-Expósito IEEE School of Electrical Engineering Guangxi UniversityNanning 530004China Department of Electrical and Computer Engineering University of MassachusettsLowellMA 01852USA State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China Laboratory of Engineering for Energy and Environmental Sustainability University of SevilleSpain

Battery energy storage systems(BESSs)are expected to play a crucial role in the operation and control of active distribution networks(ADNs).In this paper,a holistic state estimation framework is developed for ADNs with BESSs integrated.A dynamic equivalent model of BESS is developed,and the state transition and measurement equations are *** on the equivalence between the correction stage of the iterated extended Kalman filter(IEKF)and the weighted least squares(WLS)regression,a holistic state estimation framework is proposed to capture the static state variables of ADNs and the dynamic state variables of BESSs,especially the state of charge(SOC).A bad data processing method is also *** simulation results show that the proposed holistic state estimation framework improves the accuracy of state estimation as well as the capability of bad data detection for both ADNs and BESSs,providing comprehensive situational awareness for the whole system.

关键词： Active distribution network(ADN) anomaly detection battery energy storage system(BESS) Kalman filtering situational awareness state estimation state of charge(SOC)

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Design of Wave Scattering From Gain and Loss Disordered Materials

Design of Wave Scattering From Gain and Loss Disordered Mate...

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Ikbeom Lee Kunwoo Park Sunkyu Yu Department of Electrical and Computer Engineering Intelligent Wave Systems Laboratory Seoul National University Seoul Korea

We propose the design of scattering from gain and loss materials using the structure factor. Increased degrees of freedom in the structure factor allow the suppression across the target momentum space.

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

关键词： Scattering Lasers and electrooptics Electro-optical waveguides

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Speaker Extraction with Verification of Present and Absent Target Speakers

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Journal of Shanghai Jiaotong University (Science) 2025年 1-6页

作者： Zhang, Ke Borsdorf, Marvin Liu, Tianchi Wang, Shuai Wei, Yangjie Li, Haizhou Key Laboratory of Intelligent Computing in Medical Image Northeastern University Shenyang110819 China Shenzhen Guangdong518000 China Machine Listening Lab University of Bremen Bremen28359 Germany Department of Electrical and Computer Engineering National University of Singapore Singapore119077 Singapore

Target speaker extraction (TSE) models are expected to extract the target speech from a cocktail party mixture signal. When only trained with present target speaker samples (PT), these models output noise in the absence of the target speaker (AT). One may enhance the TSE quality by providing the information about the PT and AT. However, the detection of the target speaker is not perfect. In this paper, we propose a new model, TSEV, which performs target speaker extraction and speaker verification simultaneously. The TSEV model outputs an extracted speech and generates two speaker embeddings per inference to detect the target speaker. By sharing the speaker encoder and low-level modules, the speaker verification task can be performed in low signal-to-noise ratio scenarios. We train the TSEV model on multi-talker PT and AT conditions with fully overlapped speech. Experiments verify the superiority of jointly performing two tasks in the proposed model. The TSEV model achieves better verification performance without degrading the extraction performance compared with the baseline. © Shanghai Jiao Tong University 2025.

关键词： Speech recognition

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LSTM-Based Digital Twin Modeling for LVDC Microgrid Operation with Pulsed Load

LSTM-Based Digital Twin Modeling for LVDC Microgrid Operatio...

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IEEE Industry Applications Society Annual Meeting (IAS)

作者： Mahmoud S. Abdelrahman Mustafa Esoofally Hossam Hussein Ibtissam Kharchouf Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami USA

ISBN: (数字)9798350372717

ISBN: (纸本)9798350372724

Proper control and energy management is crucial for the effective, practical, and reliable operation of DC microgrids. In DC microgrids, the high certainties of renewables and the dynamic behavior of particular loads propose different modeling, operation, and control challenges. With recent advancements in information and communication technologies offering energy solution services relying on data analytics, machine learning (ML), and IoT technologies, the concept of digital twins (DT) has emerged as a feasible and active model to enhance the operation and resilience of microgrids. This paper proposes a long short-term memory (LSTM) neural networkbased strategy to construct a data-driven digital twin (DT) model of DC microgrids. The model is tested and validated with a standalone DC MG containing Renewable Energy Sources (RES), Energy Storage Sources (ESSs), and different load types. The accuracy of the created twin model is tested and evaluated under different scenarios of the microgrid operation, such as a sudden decrease in renewable generation and energizing pulsed load to the MG.

关键词： Renewable energy sources Accuracy Simulation Microgrids Real-time systems Digital twins Reliability Long short term memory Load modeling Resilience

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