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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Wu, Chih-Chiang Rout, Uma Sankar Chou, Hsin-Ping Hu, Jwu-Sheng Industrial Technology Research Institute Mechanical and Mechatronics Systems Research Laboratories Hsinchu Taiwan National Yang Ming Chiao Tung University Department of Electrical Engineering & Computer Science Hsinchu Taiwan

ISBN: (纸本)9798350376067

This paper investigates the evolving landscape of EV traction inverters, addressing key technical goals outlined by US Drive and analyzing parameters such as voltage, power density, and efficiency. Through innovative methodologies, a high-efficiency SiC-based traction inverter is developed to overcome challenges like spatial constraints. Leveraging international benchmarks, a cutting-edge SiC-based 800V 243 kW traction inverter with a power density of 60 kW/L is presented, poised to surpass US Drive's 2025 targets. This study emphasizes SiC technology's role in advancing EV propulsion systems towards sustainable and efficient transportation solutions. © 2024 IEEE.

关键词： power density silicon carbide high-efficiency sustainable transportation traction inverter

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Design of a Tube Model Predictive Controller for Pneumatic Muscle Actuators Servomechanism under Uncertainty 10

Design of a Tube Model Predictive Controller for Pneumatic M...

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10th International Conference on Control, Instrumentation and Automation, ICCIA 2024

作者： Zibandehpoor, Mobina Rahmati, Fatemeh Delrobaei, Mehdi Nikoofard, Amirhossein K. N. Toosi University of Technology Faculty of Electrical Engineering Department of Mechatronics Tehran Iran K. N. Toosi University of Technology Faculty of Electrical Engineering Department of Systems and Control Tehran Iran

ISBN: (纸本)9798331509972

Pneumatic muscle actuators (PMAs) are efficient and versatile, mimicking natural muscle-Tendon systems. They are widely used in manufacturing, automotive, and aerospace industries due to their lightweight design, high force-To-weight ratio, and flexibility, making them suitable for delicate tasks and powerful exertions. Their application in industrial and biomechatronic systems highlights their potential to revolutionize automation and human-machine interaction. This research aimed to develop a PMA regulator using the Model Predictive Control (MPC) framework. Researchers identified key PMA characteristics and defined attributes for the regulator, ensuring accurate signal tracking, effective uncertainty handling, and real-Time operation. The initial stages involved implementing a proportional-integral-derived (PID) controller, and by integrating a PID block with a linear MPC block, a tube MPC controller was developed to enhance performance. The controllers' responses were tested in noisy environments using a low-pass filter for evaluation. The tube MPC controller demonstrated optimal control, robustness, and expertise in managing uncertainties, making it a reliable choice for system control. © 2024 IEEE.

关键词： Model predictive control

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High Voltage Circuit Breaker Health Index Evaluation Considering Measurement Accuracy

High Voltage Circuit Breaker Health Index Evaluation Conside...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Asefi, Sajjad Kilter, Jako Shayesteh, Ebrahim Hilber, Patrik Lindquist, Tommie Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia Kth Royal Institute of Technology Department of Electromagnetic Engineering Stockholm Sweden Rise - Research Institutes of Sweden Department of Electric Power Systems Stockholm Sweden

ISBN: (纸本)9789531842976

The reliable operation of high voltage circuit breakers (HVCBs) is crucial for ensuring the security of the power system. Therefore, the accurate calculation of the health index (HI) for proper maintenance of HVCBs is essential. However, existing methods often neglect two key challenges: proper signal preprocessing for feature extraction and incorporating measurement accuracy into the HI model. This paper addresses these shortcomings by proposing a methodology for improving HI representation for HVCBs. We account for measurement accuracy by considering the varying precision of different monitoring schemes. Furthermore, the impact of signal preprocessing on the condition monitoring data is analyzed. Finally, a case study exhibits how the HI based failure rate can affect the reliability centered maintenance scheduling in the power system. © 2024 IEEE.

关键词： Failure rate

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Intelligent Biped Robot Simulation Locomotion using Deep Q Network 24

Intelligent Biped Robot Simulation Locomotion using Deep Q N...

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24th International Electronics Symposium, IES 2022

作者： Imaduddin, Hasan Saputra, Azhar Aulia Sulistijono, Indra Adji Kubota, Naoyuki Tokyo Metropolitan University Mechanical Systems Engineering Tokyo Japan Politeknik Elektronika Negeri Surabaya Mechatronics Engineering Surabaya Indonesia

ISBN: (数字)9781665489713

ISBN: (纸本)9781665489713

This research suggests a deep Q-network learning approach coupled with a layered neural-based locomotion. An analog signal is produced by central pattern generation (CPG) in the higher layers and sent to motor neuron pools in the lower levels. Motor neurons produce joint angular velocity in the lower levels. The neural oscillator model in the spinal cord serves as the foundation for the central pattern generation. It reacts to the pattern of the driving model. Then, using a human musculoskeletal model, the inner state of motor neurons was constructed based on muscle activation. Additionally, the motor neuron (MN) pool is linked to the sensory neuron (SN), which transmits internal feedback from the robot. A humanoid robot simulation using the proposed concept has been used to carry various loads. Adjustments to the robot's behavior to maintain its stance. © 2022 IEEE.

关键词： Anthropomorphic robots

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A survey on the visual perception of humanoid robot

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Biomimetic Intelligence & Robotics 2025年第1期5卷 3-14页

作者： Teng Bin Hanming Yan Ning Wang Milutin N.Nikolić Jianming Yao Tianwei Zhang The Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen 518172China College of Intelligent Systems Science and Engineering Harbin Engineering UniversityHarbin 150001China College of Physics and Optoelectronic Engineering Shenzhen UniversityShenzhen 518060China College of Mechatronics Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China Faculty of Technical Sciences University of Novi SadNovi Sad 21102Serbia Electronic science and technology Guangdong University of TechnologyGuangzhou 510006China

In recent years,humanoid robots have gained significant attention due to their potential to revolutionize various industries,from healthcare to manufacturing.A key factor driving this transformation is the advancement of visual perception systems,which are crucial for making humanoid robots more intelligent and *** the progress,the full potential of vision-based technologies in humanoid robots has yet to be fully *** review aims to provide a comprehensive overview of recent advancements in visual perception applied to humanoid robots,specifically focusing on applications in state estimation and environmental *** summarizing key developments and analyzing the challenges and opportunities in these areas,this paper seeks to inspire future research that can unlock new capabilities for humanoid robots,enabling them to better navigate complex environments,perform intricate tasks,and interact seamlessly with humans.

关键词： advanced technologies visual perception autonomous navigation human robot interaction environmental interaction state estimation humanoid robots advancement visual perception systemswhich

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HDLIDP: A Hybrid Deep Learning Intrusion Detection and Prevention Framework

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Computers, Materials & Continua 2022年第11期73卷 2293-2312页

作者： Magdy M.Fadel Sally M.El-Ghamrawy Amr M.T.Ali-Eldin Mohammed K.Hassan Ali I.El-Desoky Computer Engineering and Systems Department Faculty of EngineeringMansoura UniversityMansoura35516DKEgypt Head of Communications and Computer Engineering Department MISR Higher Institute for Engineering and TechnologyMansoura35111DKEgypt Mechatronics Department Faculty of EngineeringHours University in Egypt(HUE)New Damietta34517DTEgypt

Distributed denial-of-service(DDoS)attacks are designed to interrupt network services such as email servers and webpages in traditional computer ***,the enormous number of connected devices makes it difficult to operate such a network *** defined networks(SDN)are networks that are managed through a centralized control system,according to *** controller is the brain of any SDN,composing the forwarding table of all data plane network *** the advantages of SDN controllers,DDoS attacks are easier to perpetrate than on traditional *** the controller is a single point of failure,if it fails,the entire network will *** paper offers a Hybrid Deep Learning Intrusion Detection and Prevention(HDLIDP)framework,which blends signature-based and deep learning neural networks to detect and prevent *** framework improves detection accuracy while addressing all of the aforementioned *** validate the framework,experiments are done on both traditional and SDN datasets;the findings demonstrate a significant improvement in classification accuracy.

关键词： Software defined networks(SDN) distributed denial of service attack(DDoS) signature-based detection whale optimization algorism(WOA) deep learning neural network classifier

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Mn-based MXene with high lithium-ion storage capacity

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Nano Research 2024年第5期17卷 4181-4191页

作者： Yanyan Wu Dongqing Liu Xiaonan Wang Usman Ghani Muhammad Asim Mushtaq Jinfeng Yang Huarui Sun Panagiotis Tsiakaras Xingke Cai School of Science and Ministry of Industry and Information Technology Key Laboratory of Micro-Nano Optoelectronic Information System Harbin Institute of Technology ShenzhenShenzhen 5180552 China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China Institute for Advanced Study Shenzhen UniversityShenzhen 518060China College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China Laboratory of Alternative Energy Conversion Systems Department of Mechanical EngineeringSchool of EngineeringUniversity of ThessalyPedion Areos 38834Greece

3d-transition metal(Fe,Co,Ni,and Mn)-based MXene materials have been predicted to demonstrate exceptional electrochemical performance because of their good electrical conductivity and the presence of metallic atoms with multiple charge ***,until now,there have been no reports on MXenes based on Fe,Co,Ni,and Mn,due to the lack of 3d-metal-layered ***,we successfully synthesized the first 3d-transition metal-based MXenes,Mn_(2)CT_(x) by exfoliating a layered precursor derived from the anti-perovskite bulk *** as-prepared Mn_(2)CT_(x) MXene nanosheets were employed as anode materials in lithium-ion batteries,which exhibited stable storage capacity of 764.7 mAh·g^(-1) at 0.5 C,placing its storage capacities at an upper-middle level compared with other reported MXene materials as well as other Mn-based anode ***,this study opens a new avenue for MXene research by synthesizing 3d-transition metal-based MXenes for electrochemical applications.

关键词： Mn_(3)GaC Mn_(2)CT_(x) MXenes lithium-ion battery anode materials negative fading capacity

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Total Quality Management Implementation in the Mobile Network Operations Centre: A Systematic Literature Review

Total Quality Management Implementation in the Mobile Networ...

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2024 International Conference on Science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Mogase, Keabetswe Daniyan, Ilesanmi Felix, Ale Mpofu, Khumbulani Tshwane University of Technolology Department of Industrial Engineering Pretoria South Africa Achievers University Department of Mechanical & Mechatronics Engineering Owo Nigeria National Space Researcj & Development Agency Engineering & Space Systems Abuja Nigeria Tshwane University of Technology Department of Industrial Engineering Pretoria South Africa

ISBN: (纸本)9798350358155

The implementation of Total Quality Management (TQM) can enhance the operational efficiency of the telecommunication industry including the mobile network operational centres (NOC). This study employs a systematic literature review (SLR) to probe the impact of TQM on telecommunications and network operations centres (NOC) in order to establish facts and reach new conclusions. Literature is reviewed using keywords and relevant articles are selected based on the inclusion and exclusion criteria and a total of 50 articles were reviewed after the implementation of the inclusion and exclusion criteria. Thereafter, a TQM framework is developed for the NOC department, focusing on fault management of 5G transmission faults. This helps gain insights into TQM in a telecommunication NOC. It reveals what TQM tools, principles and methods that can be incorporated in the NOC for fault management of 5G transmission faults. © 2024 IEEE.

关键词： 5G mobile communication systems

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Real-time monitoring of fast gas dynamics with a single-molecule resolution by frequency-comb-referenced plasmonic phase spectroscopy

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PhotoniX 2024年第1期5卷 357-372页

作者： Duy-Anh Nguyen Dae Hee Kim Geon Ho Lee San Kim Dong-Chel Shin Jongkyoon Park Hak-Jong Choi Seung-Woo Kim Seungchul Kim Young-Jin Kim Department of Mechanical Engineering Korea Advanced Institute of Science and Technology(KAIST)Science TownDaejeon 34141South Korea Department of Mechatronic Engineering Faculty of Mechanical EngineeringHo Chi Minh City University of Technology(HCMUT)Vietnam National UniversityHo Chi Minh CityVietnam Department of Cogno-Mechatronics Engineering College of Nanoscience and NanotechnologyPusan National UniversityBusan 46241South Korea Department of Optics and Mechatronics Engineering College of Nanoscience and NanotechnologyPusan National UniversityBusan 46241South Korea School of Mechanical and Aerospace Engineering Nanyang Technological University(NTU)50 Nanyang AvenueSingapore 639798Singapore Institute of Machinery and Materials Nano-Convergence Mechanical Systems Research DivisionKorea156Gajeongbuk-RoYuseong-GuDaejeon 34103South Korea

Surface plasmon resonance(SPR)sensors are based on photon-excited surface charge density oscillations confined at metal-dielectric interfaces,which makes them highly sensitive to biological or chemical molecular bindings to functional metallic *** nanostructures further concentrate surface plasmons into a smaller area than the diffraction limit,thus strengthening photon-sample ***,plasmonic sensors based on intensity detection provide limited resolution with long acquisition time owing to their high vulnerability to environmental and instrumental ***,we demonstrate fast and precise detection of noble gas dynamics at single molecular resolution via frequency-comb-referenced plasmonic phase *** photon-sample interaction was enhanced by a factor of 3,852 than the physical sample thickness owing to plasmon resonance and thermophoresis-assisted optical confinement *** utilizing a sharp plasmonic phase slope and a high heterodyne information carrier,a small atomic-density modulation was clearly resolved at 5 Hz with a resolution of 0.06 Ar atoms per nano-hole(in 10^(11)RIU)in Allan deviation at 0.2 s;a faster motion up to 200 Hz was clearly *** fast and precise sensing technique can enable the in-depth analysis of fast fluid dynamics with the utmost resolution for a better understanding of biomedical,chemical,and physical events and interactions.

关键词： Frequency comb Nanohole array Single molecule detection Refractive index High resolution High speed Traceability to time standard

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Disaster Area Recognition from Aerial Images with Complex-Shape Class Detection

Disaster Area Recognition from Aerial Images with Complex-Sh...

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IEEE International Workshop on Safety, Security, and Rescue Robotics (SSRR)

作者： Rubén González-Navarro Dahui Lin-Yang Ricardo Vázquez-Martín Alfonso Garcia-Cerezo Robotics and Mechatronics Group Institute of Mechatronics Engineering and Cyber-physical Systems University of Malaga Spain

This paper presents a convolutional neural network (CNN) model for event detection from Unmanned Aerial Vehicles (UAV) in disaster environments. The model leverages the YOLOv5 network, specifically adapted for aerial images and optimized for detecting Search and Rescue (SAR) related classes for disaster area recognition. These SAR-related classes are person, vehicle, debris, fire, smoke, and flooded areas. Among these, the latter four classes lead to unique challenges due to their lack of discernible edges and/or shapes in aerial imagery, making their accurate detection and performance evaluation metrics particularly intricate. The methodology for the model training involves the adaptation of the pre-trained model for aerial images and its subsequent optimization for SAR scenarios. These stages have been conducted using public datasets, with the required image labeling in the case of SAR-related classes. An analysis of the obtained results demonstrates the model's performance while discussing the intricacies related to complex-shape classes. The model and the SAR datasets are publicly available.

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