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16th IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2024

作者： Shu, Jiao Xie, Zhangtian He, Xingchen Lu, Jixiang Xu, Hongsheng Wang, Ke State Grid Electric Power Research Institute State Key Laboratory of Technology and Equipment for Defense against Power System Operational Risks Nari Group Corporation Nanjing China College of Energy and Electrical Engineering Hohai University Nanjing China College of Energy and Electrical Engineering Hohai University State Key Laboratory of Technology and Equipment for Defense against Power System Operational Risks Nanjing China

ISBN: (纸本)9798350386127

This paper explores the use of Multi-Agent Generative Adversarial Imitation Learning (MAGAIL) to model and reconstruct electricity consumer behavior in demand response (DR). DR is a crucial tool for balancing supply and demand in the power system, reducing peak-hour demand, and enhancing grid reliability and flexibility. Traditional consumer behavior reconstructing models struggle with high-dimensional, nonlinear, dynamic, and highly personalized challenges. The GAIL-based method simulates expert behavior strategies and learns from historical consumer data without the need for explicit reward functions, generating strategy models that closely resemble real consumers' behavior. This paper introduces the application of GAIL in load response reconstruction and validates the model's effectiveness using real-world data from the Pennsylvania-New Jersey-Maryland (PJM) electricity market. © 2024 IEEE.

关键词： Adversarial machine learning

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Electrolytic Failure Modeling of Aluminum Electrolytic Capacitor by Finite Element Method 2

Electrolytic Failure Modeling of Aluminum Electrolytic Capac...

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2nd IEEE International Power Electronics and Application Symposium, PEAS 2023

作者： Chen, Xinrui Yao, Ran Li, Hui Lai, Wei Min, Yuan Yang, Cheng Duan, Zeyu Chen, Siyu Chongqing University State Key Laboratory of Power Transmission Equipment Technology Chongqing China Nuclear Power Institute of China Science and Technology on Reactor System Design Technology Laboratory Chengdu China

ISBN: (纸本)9798350313765

The failure rate of aluminum electrolytic capacitor (AEC) is high in power electronic systems. Due to the complex structure of AEC, it is difficult to establish an actual model, so experiments are the common way to analyze the failure of AEC. Thus, this paper proposes a finite element method (FEM) for AEC considering electrolytic failure. Firstly, the mechanism of electrolytic failure and changes of characteristic parameters in the AEC are elucidated. Secondly, an equivalent finite element model is established to simulate and analyze the electrolytic failure of AEC. Finally, the effectiveness of the proposed AEC FEM method is verified through capacitor aging experiments. © 2023 IEEE.

关键词： aluminum electrolytic capacitor (AEC) electrolytic failure finite element method (FEM)

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PFOA and PFOS induces mineralization of soil organic carbon by accelerating the consumption of dissolved organic carbon

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Carbon Research 2024年第1期3卷 1-14页

作者： Li, Yulong Lv, Bowei Chen, Zhendong Xue, Jianming Wu, Li He, Xiaoman Yang, Lie Hubei Key Laboratory of Mineral Resources Processing and Environment School of Resources and Environmental Engineering Wuhan University of Technology Wuhan430070 China Forest System POB 29237 Christchurch8440 New Zealand State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration School of Environment Northeast Normal University Changchun130117 China

The wide spread of Perfluoroalkyl substances (e.g., PFOA and PFOS) in soil can alter native soil geochemical properties and microbial communities through various approaches. Nonetheless, it is unclear that how PFOA and PFOS in soil affect the mineralization of soil organic carbon (SOC). A laboratory-scale culture experiment (180 d) was performed to explore the contribution of PFOA and PFOS to SOC dynamics and soil geochemical processes. Results showed that positive priming effect (PE) occurred in the short term (i.e., 30 days after PFOA and PFOS addition) and subsequently shifted to a slightly negative PE (i.e., 90 days) and remained in a significant negative PE thereafter (i.e., > 180 days). The PEs caused by PFOA and PFOS both accelerated the consumption of dissolved organic carbon (DOC), resulting in a significant increase in SOC mineralization (10.45%–127.36%) under the short-term incubation (30 d). As for long-term exposure (> 90 d), the organic carbon mineralization rate was significantly reduced (58.30%–65.24%) due to the excessive DOC consumption in the initial stage. High throughput analysis indicated that both PFOA and PFOS changed soil bacterial and fungal community structures, altered the relevant metabolic pathways and resulted in the enrichment of specific taxa. Graphical Abstract: (Figure presented.) © The Author(s) 2024.

关键词： Carbon emission Mineralization PFOA PFOS Selective priming

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Time-domain and Frequency-domain Analyses of PETT Oscillation in Press Pack IGBTs

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CSEE Journal of Power and Energy systems 2023年第2期9卷 682-695页

作者： Jiayu Fan Xiang Cui Xinling Tang Cheng Peng Zhibin Zhao Xiangrui Meng Xuebao Li Zhong Chen State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electrical Power UniversityBeijing 102206China Power Semiconductor Devices Research Institute State Key Laboratory of Advanced Power Transmission TechnologyGlobal Energy Interconnection Research Institute Co.Ltd.Beijing 102209China Department of Electrical Engineering University of ArkansasFayettevilleAR 72701USA

Plasma extraction transit time(PETT)oscillation might appear in IGBT devices,which is harmful to the electromagnetic compatibility(EMC)of a renewable energy *** eliminate this oscillation,its frequency-domain characteristics in wire-bonded IGBT devices have been extensively ***,the time-domain analysis of PETT oscillation,especially in Press Pack IGBT(PPI)devices,has not attracted enough attention *** this paper,PETT oscillations with multi-chips in PPI devices are systematically investigated by *** is first reported there are multiple resonant oscillations at the tail period when multi-chips turn *** overlap in the time domain waveforms,which lead PETT oscillation to be more serious in ***,PETT oscillation is divided into three different feedback states for the first *** the IGBT chip in the PETT oscillation,its physical based model and behavior model are proposed,which further form the equivalent circuit as the two-port ***,it is indicated that only parallel resonances can lead to PETT oscillation,which is consistent with experiment results.

关键词： PETT oscillation press pack IGBTs timedomain analysis two-port network

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Characteristics of laser-induced breakdown spectroscopy of liquid slag

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Plasma Science and technology 2024年第2期26卷 86-93页

作者：董长言于洪霞孙兰香李洋刘修业周平黄少文 State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016People's Republic of China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016People's RepublicofChina Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169People's Republic of China Shenyang University of Technology Shenyang 110870People's Republic of China Shenyang Ligong University Shenyang 1i0142People's Republic of China Shandong Iron and Steel Company Ltd. Jinan 271105People's Republic of China

Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-induced breakdown spectroscopy(LIBS), this study examined the effects of slag composition and temperature on the intensity and stability of the LIBS spectra. The experimental temperature was controlled at three levels: 1350℃, 1400℃, and 1450℃. The results showed that slag composition and temperature significantly affected the intensity and stability of the LIBS spectra. Increasing the Fe content and temperature in the slag reduces its viscosity, resulting in an enhanced intensity and stability of the LIBS spectra. Additionally, 42 refined slag samples were quantitatively analyzed for Fe, Si, Ca, Mg, Al, and Mn at 1350℃, 1400℃, and 1450℃.The normalized full spectrum combined with partial least squares(PLS) quantification modeling was used, using the Ca Ⅱ 317.91 nm spectral line as an internal standard. The results show that using the internal standard normalization method can significantly reduce the influence of spectral fluctuations. Meanwhile, a temperature of 1450℃ has been found to yield superior results compared to both 1350℃ and 1400℃, and it is advantageous to conduct a quantitative analysis of the slag when it is in a “water-like” state with low viscosity.

关键词： laser-induced breakdown spectroscopy(LIBS) slag temperature composition viscosity internal standard normalization partial least squares(PLS)

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EMG Based Rehabilitation Gesture Recognition Using DAE-CNN-LSTM Hybrid Model

EMG Based Rehabilitation Gesture Recognition Using DAE-CNN-L...

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2024 International Convention on Rehabilitation Engineering and Assistive technology and World Rehabilitation Robot Convention, i-CREATE and WRRC 2024

作者： Cao, Wujing Guo, Xinqiang Zou, Yupeng Zhang, Shuo Luo, Mingxiang Kobsiriphat, Worawarit Wu, Xinyu Yin, Meng Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518005 China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems China School of Mechanical Engineering China University of Petroleum China National Metal and Materials Technology Center Thailand

ISBN: (纸本)9798350355123

Stroke, as one of the leading causes of long-term disability globally, often results in motor impairments, particularly in the hands, significantly affecting patients' daily activities and causing profound psychological trauma. Rehabilitation gesture recognition, as one of the key means of active rehabilitation medicine, holds significant potential in stroke rehabilitation, providing real-time feedback on patient progress and enabling personalized interventions to meet individual needs. Traditional gesture recognition methods face numerous challenges when dealing with stroke patient data, such as noise, motion blur, and individual differences. To address these challenges, this paper proposes a novel approach for stroke patient gesture recognition using deep learning models. We adopt a strategy combining denoising autoencoder (DAE), convolutional neural network (CNN), and long short-term memory (LSTM) to enhance the accurate recognition of hand movements in stroke patients. Specifically, DAE is utilized for denoising EMG signals, extracting features, and reducing noise to improve the signal's noise resistance. CNN is employed for spatial feature extraction, while LSTM captures temporal dependencies in gesture sequences. By integrating these three deep learning models, our aim is to enhance the accuracy and robustness of rehabilitation gesture recognition. We validate the proposed method's effectiveness on an EMG dataset from seven subjects through experiments and compare it with traditional machine learning and individual CNN and LSTM algorithms. Experimental results demonstrate significant performance improvements of our hybrid model in rehabilitation gesture recognition tasks, indicating promising application prospects and practical significance. © 2024 IEEE.

关键词： Convolutional neural networks

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Comprehensive study of the ultrafast photoexcited carrier dynamics in Sb_(2)Te_(3)–GeTe superlattices

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Chinese Physics B 2024年第7期33卷 381-387页

作者：叶之江金钻明蒋叶昕卢琦贾梦辉钱冬黄夏敏李舟彭滟朱亦鸣 Terahertz Technology Innovation Research Institute Terahertz Spectrum and Imaging Technology Cooperative Innovation CenterShanghai Key Laboratory of Modern Optical SystemUniversity of Shanghai for Science and TechnologyShanghai 200093China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 200092China Key Laboratory of Artificial Structures and Quantum Control(Ministry of Education) Shenyang National Laboratory for Materials ScienceSchool of Physics and AstronomyShanghai Jiao Tong UniversityShanghai 200240China Tsung-Dao Lee Institute Shanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Precision Spectroscopy East China Normal UniversityShanghai 200062China GBA Branch of Aerospace Information Research Institute Chinese Academy of SciencesGuangzhou 510700China Guangdong Provincial Key Laboratory of Terahertz Quantum Electromagnetics Guangzhou 510700China University of Chinese Academy of Sciences Beijing 100039China

Chalcogenide superlattices Sb_(2)Te_(3)-GeTe is a candidate for interfacial phase-change memory(iPCM) data storage *** employing terahertz emission spectroscopy and the transient reflectance spectroscopy together,we investigate the ultrafast photoexcited carrier dynamics and current transients in Sb_(2)Te_(3)-GeTe *** orientation and excitation polarization dependences of the THz emission confirm that ultrafast thermo-electric,shift and injection currents contribute to the THz generation in Sb_(2)Te_(3)-GeTe *** decreasing the thickness and increasing the number of GeTe and Sb_(2)Te_(3) layer,the interlayer coupling can be enhanced,which significantly reduces the contribution from circular photo-galvanic effect(CPGE).A photo-induced bleaching in the transient reflectance spectroscopy probed in the range of~1100 nm to~1400 nm further demonstrates a gapped state resulting from the interlayer *** demonstrates play an important role in the development of iPCM-based high-speed optoelectronic devices.

关键词： Sb_(2)Te_(3)/GeTe superlattices ultrafast carrier dynamics interfacial phase change memory THz emission spectroscopy transient reflectance spectroscopy

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Ultra Flexible S-band 1x5 Wavelength Selective Switch Based On Off-the-shelf C-band Optics

Ultra Flexible S-band 1x5 Wavelength Selective Switch Based ...

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2024 Asia Communications and Photonics Conference, ACP 2024 and International Conference on Information Photonics and Optical Communications, IPOC 2024

作者： Feng, Zhenhua You, Quan Liu, Minghuan Shi, Hu Chen, Weizhang State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen China WDM System Department of ZTE Corp. Wuhan China WDM System Department of ZTE Corp. Beijing China

An S-band 1x5 WSS prototype covering 1470 to 1520 nm is experimentally demonstrated using off-the-shelf C band optical elements. The main optical performances are measured, showing comparable or even superior performa... 详细信息

ISBN: (纸本)9798350379266

关键词： Optical band gaps

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Active label-denoising algorithm based on broad learning for annotation of machine health status

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Science China(Technological Sciences) 2022年第9期65卷 2089-2104页

作者： LIU GuoKai SHEN WeiMing GAO Liang KUSIAK Andrew State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Department of Industrial and System Engineering The University of IowaSeamans CenterIowa CityIA 52242USA

Deep learning has led to tremendous success in machine maintenance and fault ***,this success is predicated on the correctly annotated *** in large industrial datasets can be noisy and thus degrade the performance of fault diagnosis *** emerging concept of broad learning shows the potential to address the label noise *** with existing deep learning algorithms,broad learning has a simple architecture and high training *** active label denoising algorithm based on broad learning(ALDBL)is ***,ALDBL captures the embedded representation from the time-frequency features by a recurrent memory ***,it augments wide features with a sparse autoencoder and projects the sparse features into an orthogonal space.A proposed corrector then iteratively changes the weights of source examples during the training and corrects the labels by using a label adaptation ***,ALDBL finetunes the model parameters with actively sampled target data with reliable pseudo *** performance of ALDBL is validated with three benchmark datasets,including 30 label denoising *** results demonstrate the effectiveness and advantages of the proposed algorithm over the other label denoising algorithms.

关键词： data annotation broad learning deep learning domain adaptation fault diagnosis noisy label

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Simultaneous enhancement of sensitivity, resonant frequency, and overload capability of piezoresistive accelerometers by heavily-doped fillet structures on sensing beams

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IEEE Sensors Journal 2025年第11期25卷 19138-19146页

作者： Xia, Yong Wang, Tao Lv, Yang Han, Xiangguang Yu, Mingzhi Tan, Renjie Huang, Mimi Jia, Chen Zhao, Libo Sun, Lin Yang, Ping Lu, Dejiang Xi'an Jiaotong University School of Mechanical Engineering State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies Xi'an710049 China Ningbo CRRC Times Transducer Technology Co. LTD Department of Basic Research and Development Ningbo315021 China Research Institute for Intelligent Sensing Technology and System School of Instrument Science and Technology State Key Laboratory for Manufacturing Systems Engineering State Industry-Education Integration Center for Medical Innovations International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies Xi'an Jiaotong University Xi'an710049 China Shandong Laboratory of Advanced Materials and green Manufacturing at Yantai Yantai264000 China

High sensitivity, high natural frequency, and high overload capability are desired for accelerometers used in industrial applications, but simultaneously enhancing all is challenging. Here, via designing novel heavily-doped fillet structures, we prove the sensitivity, resonant frequency, and overload capability can be simultaneously enhanced. The enhancements are attributed to regulations of stress concentration and effective sensing regions by the heavily-doped fillets. The sensors with and without fillets are designed, fabricated, packaged, and tested. The results show a sensitivity of 0.31±0.02 mV/g@5V, a natural frequency of 37.87±2.09 kHz, and an overload of 10040.17±531.76 g for sensors with 10-μm fillets, which are superior to 0.27±0.01 mV/g@5V, 34.13±0.90 kHz, and 7368.55±843.92 g for those no-fillet counterparts. Additionally, the developed sensor further exhibited feasibility in air-bearing vibration monitoring. The proposed design is envisioned to give insights into the novel designs of high-performance stress-based sensors, including accelerometers, pressure sensors, and strain gauges. © 2001-2012 IEEE.

关键词： Strain gages

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