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16th IET International Conference on AC and DC Power Transmission, ACDC 2020

作者： Li, Wei Liu, Bo Xiao, Fengliang Wang, Haoqing Wang, Yuanmeng Xie, Wengang Yu, Zhanqing Shandong Taikai High-Voltage Switchgear Co. Ltd. Tai'an China China Electric Power Research Institute. Beijing China State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing China

ISBN: (纸本)9781839533914

With the increase of multi-terminal flexible DC distribution network projects, medium-voltage DC circuit breaker, as the key equipment to remove DC short-circuit fault, plays a key role in the operation reliability of the whole DC distribution network. In order to meet the engineering needs of DC distribution network, a 10kV hybrid DC circuit breaker based on the coupling negative voltage principle is developed in this paper. Firstly, the topology and working principle of the DC circuit breaker are introduced. Furthermore, the design scheme of key components including fast mechanical switch, power electronic switch and coupling negative voltage device is given. Finally, a 10kV hybrid DC circuit breaker prototype is developed and tested. The results show that the 10kV hybrid DC circuit breaker can break 15kA short circuit current within 2ms, and has the characteristics of low loss and high reliability. © 2020 Institution of engineering and Technology. All rights reserved.

关键词： Electric circuit breakers

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3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video

arXiv

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arXiv 2021年

作者： Wang, Guangming Zhong, Jiquan Zhao, Shijie Wu, Wenhua Liu, Zhe Wang, Hesheng Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China Department of Engineering Mechanics Shanghai Jiao Tong University Shanghai200240 China Department of Computer Science and Technology University of Cambridge CambridgeCB2 1TN United Kingdom

Depth and ego-motion estimations are essential for the localization and navigation of autonomous robots and autonomous driving. Recent studies make it possible to learn the per-pixel depth and ego-motion from the unlabeled monocular video. A novel unsupervised training framework is proposed with 3D hierarchical refinement and augmentation using explicit 3D geometry. In this framework, the depth and pose estimations are hierarchically and mutually coupled to refine the estimated pose layer by layer. The intermediate view image is proposed and synthesized by warping the pixels in an image with the estimated depth and coarse pose. Then, the residual pose transformation can be estimated from the new view image and the image of the adjacent frame to refine the coarse pose. The iterative refinement is implemented in a differentiable manner in this paper, making the whole framework optimized uniformly. Meanwhile, a new image augmentation method is proposed for the pose estimation by synthesizing a new view image, which creatively augments the pose in 3D space but gets a new augmented 2D image. The experiments on KITTI demonstrate that our depth estimation achieves state-of-the-art performance and even surpasses recent approaches that utilize other auxiliary tasks. Our visual odometry outperforms all recent unsupervised monocular learning-based methods and achieves competitive performance to the geometry-based method, ORB-SLAM2 with back-end optimization. Copyright © 2021, The Authors. All rights reserved.

关键词： Robots

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PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN with Dual-Discriminators

arXiv

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arXiv 2023年

作者： Cong, Runmin Yang, Wenyu Zhang, Wei Li, Chongyi Guo, Chun-Le Huang, Qingming Kwong, Sam Institute of Information Science Beijing Jiaotong University Beijing100044 China School of Control Science and Engineering Shandong University Jinan250061 China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan250061 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China College of Computer Science Nankai University Tianjin300350 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Peng Cheng Laboratory Shenzhen518055 China Department of Computer Science City University of Hong Kong Hong Kong City University of Hong Kong Shenzhen Research Institute Shenzhen51800 China

Due to the light absorption and scattering induced by the water medium, underwater images usually suffer from some degradation problems, such as low contrast, color distortion, and blurring details, which aggravate the difficulty of downstream underwater understanding tasks. Therefore, how to obtain clear and visually pleasant images has become a common concern of people, and the task of underwater image enhancement (UIE) has also emerged as the times require. Among existing UIE methods, Generative Adversarial Networks (GANs) based methods perform well in visual aesthetics, while the physical model-based methods have better scene adaptability. Inheriting the advantages of the above two types of models, we propose a physical model-guided GAN model for UIE in this paper, referred to as PUGAN. The entire network is under the GAN architecture. On the one hand, we design a Parameters Estimation subnetwork (Par-subnet) to learn the parameters for physical model inversion, and use the generated color enhancement image as auxiliary information for the Two-Stream Interaction Enhancement subnetwork (TSIE-subnet). Meanwhile, we design a Degradation Quantization (DQ) module in TSIE-subnet to quantize scene degradation, thereby achieving reinforcing enhancement of key regions. On the other hand, we design the Dual-Discriminators for the style-content adversarial constraint, promoting the authenticity and visual aesthetics of the results. Extensive experiments on three benchmark datasets demonstrate that our PUGAN outperforms state-of-the-art methods in both qualitative and quantitative metrics. The code and results can be found from the link of https://***/proj_***. © 2023, CC BY-NC-SA.

关键词： Discriminators

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Excellent electrical properties of zinc-oxide varistors by tailoring sintering process for optimizing line-arrester configuration 7

Excellent electrical properties of zinc-oxide varistors by t...

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7th IEEE International Conference on High Voltage engineering and Application, ICHVE 2020

作者： Meng, Pengfei Cao, Wei Chen, Chao Wan, Shuai Xu, Heng Hu, Jun He, Jinliang Tsinghua University Department of Electrical Engineering Beijing China Wuhan Nari Limited Liability Company State Grid Electric Power Research Institute Wuhan China Guangdong Aikang Electric Power Co. Ltd Guangzhou China State Key Laboratory of Control and Simulation of Power System and Generation Equipment Tsinghua University Department of Electrical Engineering Beijing China

ISBN: (纸本)9781728155111

We optimized the excellent electrical performance of zinc-oxide (ZnO) varistors doping of aluminum and indium by tailoring the sintering process. The surface morphology, nonlinear volt ampere properties, capacitance-voltage characteristics, and dielectric analyses were carried out. At a given aluminum and indium concentration, the average sample grain size (d) increased as lengthening sintering time from 0.5 to 2.5 h. The voltage gradient (E_{1\{mA}}) decreased from 602.4 V/mm to 356.7 V/mm. The residual voltage of the sintered varistors at the lightning impulse current (8/20\ \mu\mathrm{s}) decreased as the samples sintering holding time extended from 0.5 to 2.0 h. When the ZnO varistor was sintered for 1.5 h, the samples showed an excellent performance, with a reference voltage of 479.3 V/mm at 1 mA DC. When assembled in the line surge arresters, the obtained high-voltage-gradient ZnO varistors can decrease their length and residual voltage, which allows for better coordination of the line surge arrester with the insulators. This study has great significance to optimize line-arrester configurations and improve power-system stability. © 2020 IEEE.

关键词： Sintering

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Deep reinforcement learning-assisted large neighborhood search for online scheduling large-scale emergency tasks to Earth-observing satellites

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Expert systems with Applications 2025年 291卷

作者： Jing Qi Min Hu Lining Xing Zhenhua Su Department of Aerospace Science and Technology Space Engineering University Beijing 101416 PR China DFH Satellite Co. Ltd. Beijing 100094 PR China Research Institute of Intelligent Control and Manufacturing System Jiangsu University of Technology Changzhou 213001 PR China

Recent mushrooming of Earth-observing satellites provides richer services to a growing subscribers, including enterprises, governmental bodies, and military sectors. Scheduling tasks to Earth-observing satellites rationally is crucial for fulfilling user requirements, and has experienced vigorous development. Unfortunately, online scheduling of large-scale emergency tasks remains a complicated ongoing issue. Considering this, we propose integrating deep reinforcement learning and large neighborhood search (IDRLNS, for short) with two novel features. First, we transform the process of mapping tasks to resources in deep reinforcement learning models into two sub-processes: task sequence and resource selection, striving to compress the exponentially exploding search space as the task increases. Then, we leverage the characteristics of both Earth-observing satellites and tasks to design three problem-specific destroy and repair operators to further improve the optimization efficiency of the large neighborhood search. We evaluate our proposed algorithm against three representative algorithms using data collected from realistic orbits and applications. The experimental results demonstrate that IDRLNS achieves over 7.76 % more reward, while also keeping a faster convergence speed.

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Performance evaluation of the natural gas combined cycle with various hydrogen co-firing rates

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Energy Conversion and Management 2025年 341卷

作者： Hyeonrok Choi Youngjae Lee Won Yang Changkook Ryu Seong-il Kim Low-Carbon Emission Control R&D Department Research Institute of Sustainable Development Technology Korea Institute of Industrial Technology Cheonan 31056 Republic of Korea School of Mechanical Engineering Sungkyunkwan University Suwon 16419 Republic of Korea Green Process and Energy System Engineering University of Science and Technology Cheonan Chungnam Republic of Korea

Hydrogen is a promising carbon-free fuel for reducing CO 2 emissions in power generation and is increasingly being integrated into gas turbine combined cycle (GTCC) systems. This study evaluates the thermal performance of a 600-MWe-class GTCC plant under hydrogen co-firing by analyzing two idealized operational scenarios—fixed turbine inlet temperature (TIT) and fixed gas turbine (GT) output—and additionally proposes a load-following strategy that maintains constant total GTCC output. A process simulation model was used to assess the impact of hydrogen blending on GT performance, flue gas composition, and the bottoming cycle—including the heat recovery steam generator (HRSG) and steam turbine (ST)—under three ambient conditions. Hydrogen co-firing introduced a performance trade-off: GT efficiency improved due to favorable combustion properties, while ST output decreased owing to degraded HRSG heat transfer. Under the fixed TIT scenario, GT efficiency increased with minor reductions in ST output. In contrast, under fixed GT output, TIT and turbine exit temperature (TET) declined, significantly reducing steam temperature and ST output, especially at high hydrogen blending ratios. The greatest performance degradation occurred under the lowest TIT condition. To address this trade-off, an additional scenario was developed by regulating TIT to adjust the GT/ST power split and maintain constant GTCC output. This approach resulted in thermal efficiency gains of up to 0.72 percentage points. The proposed model incorporates radiative and convective heat transfer mechanisms and captures the key thermophysical effects of hydrogen-rich combustion gas, offering practical insights for stable and efficient GTCC operation under hydrogen co-firing conditions.

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3-D Multi-player Pursuit-evasion Game with a Faster Evader

3-D Multi-player Pursuit-evasion Game with a Faster Evader

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第三十九届中国控制会议

作者： Xu Fang Cheng Cheng Lihua Xie School of Electrical and Electronic Engineering Nanyang Technological University Department of Control Science and Engineering Tongji University Shanghai Research Institute for Intelligent Autonomous System Tongji University

This paper studies two kinds of multi-player pursuit-evasion games in 3-D space: Two-pursuer one-evader game and multi-pursuer one-evader game. The main challenges are that the evader has faster speed than a group of pursuers and the moving directions of the pursuers and faster evader are unknown to each other. First, the concept of occupied angle is introduced to represent the dominated spaces by the pursuers. Then, escape algorithm and pursuit algorithm are designed for the evader and pursuers, respectively. Finally, escape condition and capture condition of the faster evader and pursuers are presented. Some simulation examples are given to illustrate the theoretical results.

关键词： 3-D Space Pursuit-evasion Game Faster Evader Unknown Moving Direction

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HASN:A Hierarchical Attack Surface Network for system Security Analysis

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China Communications 2019年第5期16卷 137-157页

作者： Kangyu Huang Lin Yang Renfang Fu Shengli Zhou Zheng Hong College of Command and Control Engineering Army Engineering UniversityNanjing 210007China China Electronic Equipment & System Engineering Corporation Beijing 100141China State Grid Jiangsu Electric Power Company Research Institute Nanjing 210019China Information Department of Zhejiang Police College Hangzhou 310053China

Attack surfaces, as one of the security models, can help people to analyse the security of systems in cyberspace, such as risk assessment by utilizing various security metrics or providing a cost-effective network hardening solution. Numerous attack surface models have been proposed in the past decade,but they are not appropriate for describing complex systems with heterogeneous components. To address this limitation, we propose to use a two-layer Hierarchical Attack Surface Network(HASN) that models the data interactions and resource distribution of the system in a component-oriented view. First, we formally define the HASN by extending the entry point and exit point framework. Second, in order to assess data input risk and output risk on the HASN, we propose two behaviour models and two simulation-based risk metrics. Last, we conduct experiments for three network systems. Our experimental results show that the proposed approach is applicable and effective.

关键词： attack surface security analysis security model risk assessment

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Anomaly Detection of Marine Diesel Engine Valve system based on Mahalanobis Distance

Anomaly Detection of Marine Diesel Engine Valve System based...

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2020 Global Reliability and Prognostics and Health Management, PHM-Shanghai 2020

作者： Sun, Yue Xu, Aidong Wang, Kai Jia, Shuli Guo, Haifeng Han, Xiaojia Laboratory of Industrial Control Network and System State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Shenyang China Automation Engineering Department Shanghai Marine Diesel Engine Research Institute Shanghai China

ISBN: (纸本)9781728159454

Diesel engine is an important energy equipment. The valve system is the core component of diesel engine with high failure rate. It is of great significance to study the abnormal detection method of the diesel engine valve system and realize the failure warning before the failure occurs for avoiding the unexpected shutdown of the diesel engine. In this paper, an anomaly detection method of marine diesel engine valve system based on Mahalanobis distance (MD) is proposed. The failure mode of diesel engine system is analyzed. Three thermal parameters are selected as monitoring parameters for the failure mode of roller fragmentation. Fault features are extracted by MD method and the failure threshold is determined by Box-Cox transformation. Finally, the effectiveness of the proposed method is verified by the durability test of diesel engine. © 2020 IEEE.

关键词： Diesel engines

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Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

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The Lancet 2023年第10397期402卷 203-234页

作者： Ong, Kanyin Liane Stafford, Lauryn K. McLaughlin, Susan A. Boyko, Edward J. Vollset, Stein Emil Smith, Amanda E. Dalton, Bronte E. Duprey, Joe Cruz, Jessica A. Hagins, Hailey Lindstedt, Paulina A. Aali, Amirali Abate, Yohannes Habtegiorgis Abate, Melsew Dagne Abbasian, Mohammadreza Abbasi-Kangevari, Zeinab Abbasi-Kangevari, Mohsen ElHafeez, Samar Abd Abd-Rabu, Rami Abdulah, Deldar Morad Abdullah, Abu Yousuf Md Abedi, Vida Abidi, Hassan Aboagye, Richard Gyan Abolhassani, Hassan Abu-Gharbieh, Eman Abu-Zaid, Ahmed Adane, Tigist Demssew Adane, Denberu Eshetie Addo, Isaac Yeboah Adegboye, Oyelola A. Adekanmbi, Victor Adepoju, Abiola Victor Adnani, Qorinah Estiningtyas Sakilah Afolabi, Rotimi Felix Agarwal, Gina Aghdam, Zahra Babaei Agudelo-Botero, Marcela Arriagada, Constanza Elizabeth Aguilera Agyemang-Duah, Williams Ahinkorah, Bright Opoku Ahmad, Danish Ahmad, Rizwan Ahmad, Sajjad Ahmad, Aqeel Ahmadi, Ali Ahmadi, Keivan Ahmed, Ali Ahmed, Luai A. Ahmed, Syed Anees Ajami, Marjan Akinyemi, Rufus Olusola Al Hamad, Hanadi Al Hasan, Syed Mahfuz AL-Ahdal, Tareq Mohammed Ali Alalwan, Tariq A. Al-Aly, Ziyad AlBataineh, Mohammad T. Alcalde-Rabanal, Jacqueline Elizabeth Alemi, Sharifullah Ali, Hassam Alinia, Tahereh Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Amare, Firehiwot Ameyaw, Edward Kwabena Amiri, Sohrab Amusa, Ganiyu Adeniyi Andrei, Catalina Liliana Anjana, Ranjit Mohan Ansar, Adnan Ansari, Golnoosh Ansari-Moghaddam, Alireza Anyasodor, Anayochukwu Edward Arabloo, Jalal Aravkin, Aleksandr Y. Areda, Demelash Arifin, Hidayat Arkew, Mesay Armocida, Benedetta Arnlov, Johan Artamonov, Anton A. Arulappan, Judie Aruleba, Raphael Taiwo Arumugam, Ashokan Aryan, Zahra Asemu, Mulu Tiruneh Asghari-Jafarabadi, Mohammad Askari, Elaheh Asmelash, Daniel Astell-Burt, Thomas Athar, Mohammad Athari, Seyyed Shamsadin Atout, Maha Moh'd Wahbi Avila-Burgos, Leticia Awaisu, Ahmed Azadnajafabad, Sina Darshan, B.B. Babamohamadi, Hassan Badar, Muhammad Badawi, Alaa Badiye, Ashish D. Baghcheghi, Nayereh Baghe Institute for Health Metrics and Evaluation School of Medicine General Medicine Service Department of Veterans Affairs Seattle WA United States Department of Health Metrics Sciences School of Medicine Faculty of Medicine France Department of Clinical Governance and Quality Improvement Aleta Wondo Hospital Aleta Wondo Ethiopia Department of Nursing Woldia University Woldia Ethiopia Department of Nursing Department of Orthopedic Surgery Orthopaedic Surgery Social Determinants of Health Research Center Non-communicable Diseases Research Center Epidemiology Department Evidence-Based Practice Center Community and Maternity Nursing Unit University of Duhok Duhok Iraq School of Planning Faculty of Environment Department of Public Health Sciences Penn State College of Medicine Pennsylvania State University Hershey PA United States Biocomplexity Institute Virginia Tech Blacksburg VA United States College of Medicine Department of Public Health Laboratory Technology Sciences Department Department of Family and Community Health University of Health and Allied Sciences Ho Ghana Research Center for Immunodeficiencies Department of Biosciences and Nutrition Karolinska University Hospital Huddinge Sweden Clinical Sciences Department Department of Surgery Department of Surgery Department of Obstetrics & Gynecology College of Graduate Health Sciences University of Tennessee Memphis TN United States Department of Obstetrics & Gynecology Department of Clinical and Psychosocial Epidemiology Department of Anesthesia and Critical Care Centre for Social Research in Health Quality and Systems Performance Unit Cancer Institute NSW Sydney NSW Australia Department of Public Health and Tropical Medicine HIV and Infectious Diseases Department Jhpiego Abuja Nigeria Adolescent Research and Care Department Adolescent Friendly Research Initiative and Care Ado Ekiti Nigeria Department of Epidemiology Department of Epidemiology and Medical Statistics Department of Family Medicine McMaster University

Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined;these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs;defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims;type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative r

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