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Thermosense: Thermal Infrared Applications XLV 2023

作者： Plastropoulos, Angelos Adiuku, Ndidiamaka Avdelidis, Nicolas P. Ibarra-Castanedo, Clemente Maldague, Xavier P.V. Servais, Pierre Integrated Vehicle Health Management Centre School of Aerospace Transport and Manufacturing Cranfield University United Kingdom Computer Vision & Systems Laboratory Department of Electrical & Computer Engineering Laval University Quebec CityG1V 0A6 Canada NDT PRO Srl Le grand enclos 18 LibramontB6800 Belgium

ISBN: (纸本)9781510661868

Infrared thermography is a condition monitoring technique that, from a measurement of the radiant heat pattern emitted by a material, is able to determine regions or points of increased or reduced heat emission that can indicate the presence of an imperfection in the investigated material. The result of an infrared thermographic investigation is a sequence of thermograms or thermal images, in other words a picture of temperature, that can be further processed for qualitative and quantitative purposes. Such images can be presented in either false color or black and white format. In the present work, the philosophy and history of thermal–infrared imaging are reviewed. Moreover, the different evaluation approaches (passive and active), as well as many standards related to infrared thermography are discussed. Finally, various applications of the transient thermography approach are briefly presented. © 2023 SPIE.

关键词： Thermography (imaging)

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Two-Stage Representation Refinement Based on Convex Combination for 3-D Human Poses Estimation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6500-6508页

作者： Chen, Luefeng Cao, Wei Zheng, Biao Wu, Min Pedrycz, Witold Hirota, Kaoru China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Macau University of Science and Technology Institute of Systems Engineering Taipa999078 China Istinye University Research Center of Performance and Productivity Analysis Istanbul34010 Turkey Tokyo Institute of Technology Yokohama226-8502 Japan

In the human pose estimation task, on the one hand, 3-D pose always has difficulty in dividing different 2-D poses if the view is limited;on the other hand, it is hard to reduce the lifting ambiguity because of the lack of depth information, it is an important and challenging problem. Therefore, two-stage representation refinement based on the convex combination for 3-D human pose estimation is proposed, in which the two-stage method includes a dense-spatial-temporal convolutional network and a local-to-refine network. The former is applied to determine the features between each video frame;the latter is used to get the different scales of pose details. It aims to address the difficulty of estimating 3-D human pose from 2-D image sequences. In such a way, it can better use the relations between every frame in the sequence of the pose video to produce more accurate results. Finally, we combine the above network with a block called convex combination to help refine the 3-D pose location. We test the proposed approach on both Human3.6m and MPII datasets. The result confirms that our method can achieve better performance than improved CNN supervision, a simple yet effective baseline, and coarse-to-fine volumetric prediction. Besides, a robustness test experiment is carried out for the proposed method while the input is interrupted. The result verifies that our method shows better robustness. © 2024 IEEE.

关键词： Convolution

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Spontaneous Emergence of Multitasking Robotic Swarms

Spontaneous Emergence of Multitasking Robotic Swarms

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Zhang, Ji Liang, Yiming Zhu, Shiqiang Xiang, Tian Zhu, Hongwei Gu, Jason Song, Wei Li, Tiefeng Zhejiang Lab Hangzhou310027 China Dalhousie Universit Department of Electrical and Computer Engineering Halifax Canada State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou310027 China

ISBN: (纸本)9781665481090

Robot swarms promise to replace humans in complex scenarios like resource exploration, environmental monitoring, and military missions. These complex scenarios require robots to be able to complete multiple tasks at the same time adaptively. From the point of view of statistical mechanics, the phenomenon of the multiply states of a given system is a kind of partial synchronization. Inspired by biological groups such as flocks of birds and schools of fish, we model the robots as self-propelled particles with Kuramoto-Sakaguchi like interactions. We uncover the state of the robot swarm can be manipulated using the phase lag of the Kuramoto-Sakaguchi like interactions. The system is partially synchronized at the edge between order and disorder, and the robots present two distinguished motion patterns, one is completely periodic movement, and the other one is chaos. This study provides new insights into the collaboration of robot swarms. © 2022 IEEE.

关键词： Statistical mechanics

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An Evolutionary Ising Optimization Framework for Unconstrained Binary Quadratic Programming

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IEEE Transactions on Evolutionary Computation 2025年

作者： Fu, Wujie Trivedi, Anupam Chen, Guanyu Gao, Yuan Srinivasan, Dipti Danner, Aaron National University of Singapore NUS graduate school Singapore Singapore National University of Singapore Department of Electrical and Computer Engineering Singapore Singapore Chongqing University Key Laboratory of Optoelectronic Technology and Systems College of Optoelectronic Engineering Chongqing China

An Ising machine (IM), as a type of analog computer tailored for tackling intractable combinatorial optimization problems, has attracted remarkable attention in recent years. In contrast to the blossoming field of bespoke IM hardware, developing metaheuristics from IMs remains largely uninvestigated. Here, we propose a physics-inspired evolutionary computation paradigm, termed the Ising optimization framework (IOF);it comprises a unique Ising algorithm and a hybrid annealing scheme, which together are well-suited for solving quadratic unconstrained binary optimization (QUBO) problems embedded in Ising system energy. The Ising algorithm leverages a set of iterated self-mapping functions to evolve an Ising-spin swarm, enabling efficient energy minimization in artificial Ising systems while mitigating detrimental chaos. Complementing the algorithm, a hybrid annealing scheme integrating singular value dropout, bifurcation control, and a nudging strategy, is devised to augment the overall optimization capacity. The effectiveness of the IOF is validated on various Ising and Max-cut problems with decision variables ranging from 625 to 5000 in number. In comparison to four major types of methods for solving QUBOs, including IM simulations, nature-inspired algorithms, a state-of-the-art heuristic, and the commercial solver Gurobi, the IOF consistently demonstrates notable optimization quality and computational efficiency. This paper provides a theoretical foundation and practical guidelines for bridging Ising-inspired approaches with evolutionary computation, offering an evolutionary perspective on Ising optimizations and suggesting a fertile avenue for future research and application. © 1997-2012 IEEE.

关键词： Ising model

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A Multi-layer Non-Terrestrial Networks Architecture for 6G and Beyond under Realistic Conditions and with Practical Limitations

arXiv

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arXiv 2025年

作者： Khennoufa, Faical Abdellatif, Khelil Yanikomeroglu, Halim Ozturk, Metin Elganimi, Taissir Kara, Ferdi Rabie, Khaled LGEERE Laboratory Department of Electrical Engineering Echahid Hamma Lakhdar University El-Oued Algeria Laboratory Department of Systems and Computer Engineering Carleton University OttawaONK1S 5B6 Canada Electrical and Electronics Engineering Ankara Yıldırım Beyazıt University Ankara Turkey The Department of Electrical and Electronic Engineering University of Tripoli Libya The Department of Computer Engineering Zonguldak Bulent Ecevit University Zonguldak Turkey Division of Communications Systems KTH Royal Institute of Technology Sweden The Department of Computer Engineering King Fahd University of Petroleum and Minerals Saudi Arabia

In order to bolster the next generation of wireless networks, there has been a great deal of interest in non-terrestrial networks (NTN), including satellites, high altitude platform stations (HAPS), and uncrewed aerial vehicles (UAV). To unlock their full potential, these platforms can integrate advanced technologies such as reconfigurable intelligent surfaces (RIS) and next-generation multiple access (NGMA). However, in practical applications, transceivers often suffer from radio frequency (RF) impairments, which limit system performance. In this regard, this paper explores the potential of multi-layer NTN architecture to mitigate path propagation loss and improve network performance under hardware impairment limitations. First, we present current research activities in the NTN framework, including RIS, multiple access technologies, and hardware impairments. Next, we introduce a multi-layer NTN architecture with hardware limitations. This architecture includes HAPS super-macro base stations (HAPS-SMBS), UAVs–equipped with passive or active transmissive RIS–, and NGMA techniques, like non-orthogonal multiple access (NOMA), as the multiple access techniques to serve terrestrial devices. Additionally, we present and discuss potential use cases of the proposed multi-layer architecture considering hardware impairments. The multi-layer NTN architecture combined with advanced technologies, such as RIS and NGMA, demonstrates promising results;however, the performance degradation is attributed to RF impairments. Finally, we identify future research directions, including RF impairment mitigation, UAV power management, and antenna designs. © 2025, CC0.

关键词： Unmanned aerial vehicles (UAV)

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Impact and Mitigation of Electromagnetic Interference Between HVTL and Pipelines

Impact and Mitigation of Electromagnetic Interference Betwee...

引用

IEEE Southeastcon

作者： Hossam Hussein Abd El-Latif S. Ahmed Sabry Mousa El-Sayed M. El-Refaie Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami USA Department of Electrical Power and Machines Engineering Faculty of Engineering Helwan University Cairo Egypt

High-voltage transmission lines transmit bulk power from one place to another and may pass through densely populated areas or forests, causing an economic challenge. While following the right-of-way (ROW) rules, high-voltage transmission lines are forced to share the same corridors with others, like metallic gas pipelines. In this regard, the electromagnetic fields from high-voltage transmission lines will affect neighboring pipelines using inductive, conductive, and capacitive effects. As a result, there will be an induced voltage across the metallic pipes, which will have negative repercussions. An example of this includes corrosion in the pipeline itself and those in direct contact with the pipeline via touch and step voltages. This paper studies the electromagnetic interference for the El-Fayoum-Dahshour gas pipeline, which shares the same route for 72 km with three overhead transmission lines, two of which are 500 kV and the third is 220 kV. Several study cases were done to show the impact of soil resistivity variation on the pipeline-induced voltage. The results conclude that the LG fault is the worst-case scenario. Moreover, mitigating the total induced voltage to the recommended safe limits was achieved by applying the polarization cell method.

关键词： Power transmission lines Pipelines Electromagnetic interference Voltage High-voltage techniques Forestry Soil

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Learning Reduced-Order Linear Parameter-Varying Models of Nonlinear systems ⁎

引用

IFAC-PapersOnLine 2024年第15期58卷 265-270页

作者： Patrick J.W. Koelewijn Rajiv Singh Peter Seiler Roland Tóth Sioux Technologies B.V. Eindhoven The Netherlands Control Systems Group Eindhoven University of Technology Eindhoven The Netherlands The MathWorks Inc. Natick USA Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor USA Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

In this paper, we consider the learning of a Reduced-Order Linear Parameter-Varying Model (ROLPVM) of a nonlinear dynamical system based on data. This is achieved by a two-step procedure. In the first step, we learn a projection to a lower dimensional state-space. In step two, an LPV model is learned on the reduced-order state-space using a novel, efficient parameterization in terms of neural networks. The improved modeling accuracy of the method compared to an existing method is demonstrated by simulation examples.

关键词： Reduced-order modeling Neural Networks Linear Parameter-Varying Models

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Currents in a HV cable in the presence of a conductive contaminant 2

Currents in a HV cable in the presence of a conductive conta...

引用

2nd International Conference on Advanced electrical engineering, ICAEE 2022

作者： Boudiaf, A. Bouazabia, S. Harid, N. Houari Boumediène University of Science and Technology Electric and Industrial Systems Laboratory Algiers Algeria Khalifa University of Science and Technology Department of Electrical and Computer Engineering Abu Dhabi United Arab Emirates

ISBN: (数字)9781665417419

ISBN: (纸本)9781665417419

The presence of a conductive contaminant within the insulation of a high voltage cable is at the origin of a conduction current likely to heat the insulation and lead to its *** the gas cavity (insulating defect), a very small conductive contaminant generates a very high electrical electric field. These fields are harmful and favor the creation of electrical trees. © 2022 IEEE.

关键词： Deterioration

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Skeleton-based Action Recognition Using Two-stream Graph Convolutional Network with Pose Refinement 41

Skeleton-based Action Recognition Using Two-stream Graph Con...

引用

第41届中国控制会议

作者： Biao Zheng Luefeng Chen Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Department of Electrical and Computer Engineering University of Alberta Tokyo Institute of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the development of science and technology,graph convolutional network has made great progress in improving the accuracy of action ***,there still exists some deficiencies in current ***,the human skeleton point coordinates entering into the network are barely refined,which may cause large ***,the second-order information(the length and direction of bones),which can reflect action characteristics discriminatively,is rarely *** solve the above issues,a two stream graph convolutional network with pose refinement for skeleton based action recognition is ***,we use an adaptive block to to help improve the *** test our method on Kinetics dataset and the experiment show it can get better results than some recent methods,which plays a positive role in future research.

关键词： Graph convolutional network Pose refinement Skeleton based action recognition Adaptive block

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Evaluation of Horizon of Viability Optimization Engine for Sustained Power to Critical Infrastructure

Evaluation of Horizon of Viability Optimization Engine for S...

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2022 IEEE Power and Energy Conference at Illinois, PECI 2022

作者： Khatana, Vivek Chakraborty, Soham Saraswat, Govind Lundstorm, Blake Salapaka, Murti V. University of Minnesota Department of Electrical and Computer Engineering United States Power Systems Engineering Center National Renewable Energy Laboratory GoldenCO80401 United States Enphase Energy AustinTX78758 United States

ISBN: (纸本)9781665402293

In the aftermath of increasingly frequent catastrophic events, a typical scenario is critical infrastructure (CI) units being supported by available backup sources with a weak power grid that can be intermittent or absent. Such a scenario is significantly challenging in the sense of providing reliable supply of power to CI units. In this article, an intelligent optimization scheme, termed a horizon of viability (HoV) engine, is developed to guarantee the viability of a sustained, reliable supply of power to the CI units over a time horizon. The proposed HoV engine generates a cost-optimal portfolio of the locally available generation sources and the loads over a time horizon using a mixed-integer convex programming problem. A controller-hardware-in-the-loop (CHIL) platform is developed to evaluate the control performance of the HoV engine. The experimental results corroborate the efficacy in maintaining the viability of the CI units after a grid interruption event. Further, the proposed HoV optimization scheme performs better than existing net-load management schemes in the literature. © 2022 IEEE.

关键词： Critical infrastructures

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