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6th International Conference on Vocational Education and electrical engineering, ICVEE 2023

作者： Ali, Salim A. Ajel, Ahmed R. Ghadhban, Safaa A. Middle Technical University Electrical Engineering Technical College Department of Electrical Power Engineering Techniques Baghdad Iraq Middle Technical University Electrical Engineering Technical College Department of Medical Devices Techniques Engineering Baghdad Iraq Middle Technical University Electrical Engineering Technical College Department of Control and Automation Techniques Engineering Baghdad Iraq

ISBN: (纸本)9798350326642

The study investigates the challenges posed by' partial shading conditions' (PSCs) on a performance and efficiency of solar photovoltaic (PV) systems. The primary goal is to find the best photovoltaic array setup to optimize power output while reducing efficiency losses caused by mismatching. The researchers evaluate various PV configurations such as Series (S), Series-Parallel (SP), Total Cross Tied (TCT), Bridge Linked (BL), Honey Comb (HC), and a hybrid of TCT and BL called TCT-BL, focusing on a 4x4 array layout. Six different shading patterns are examined, including diagonal, 'short and narrow', 'short and wide', 'long and narrow', 'long and wide', and random. Based on simulations using Matlab/Simulink and a 130W PV module model, the study suggests that the TCT-BL configuration offers superior power generation, efficiency, and reduced mismatching loss compared to other configurations under most PSCs examined. © 2023 IEEE.

关键词： Efficiency

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New Hysteresis control Block for Shunt Active Power Filter for Harmonics Compensation Generated by CFLs with PQ Theory 1

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2nd International Conference on Green Energy Conversion System, ICGECS 2023

作者： Hajjej, Mohamed Sbita, Lassaad El Aroudi, Abdelali Mandal, Kuntal Research Laboratory of Process Energies Environment and Electrical Systems National Engineering School of Gabes University of Gabes Zrig Eddakhlania6029 Tunisia Department of Electronics Electrical Engineering and Automatic Control Universitat Rovira i Virgili Tarragona Spain

ISBN: (数字)9789819761487

ISBN: (纸本)9789819761470

This paper proposes a New Modulation Hysteresis control block for a three phase four wire Shunt Active Power Filter (SAPF) for currents harmonics compensation generated by Compact Fluorescents Lamps (CFLs). This study employs the PQ power control strategy. The performance of the SAPF is evaluated under both simple hysteresis controller and under the new modulation hysteresis controller conditions using the Matlab/Simulink platform. The findings simulation results demonstrate that the proposed new technique can improve the power quality of the main, and the total harmonic distortion (THD) optimization, which also confirms the effectiveness of the approach. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Harmonic analysis

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Optimizing Thermo-Electric Generation with Quasi-Z-Source Converter in Energy Harvesting for Wearable Devices 3

Optimizing Thermo-Electric Generation with Quasi-Z-Source Co...

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3rd International Conference on Mechatronics and automation Technology, ICMAT 2024

作者： Lotfy, Mostafa Wageh Hussein, Aziza I. Dept. of Process Control Technology Faculty of Technology and Education Beni-Suef University Beni-Suef Egypt Electrical and Computer Engineering Department College of Engineering Effat University Jeddah Saudi Arabia

ISBN: (纸本)9781643685649

Recent advances in semiconductors industry and microelectronics have created new opportunities for integrating various technologies in energy harvesting projects. These advancements have simplified the process of capturing energy from different sources, such as thermal energy, and converting it into electrical power. Thermo-Electric Generators (TEGs) are commonly used in many applications such as wearable devices. However Thermo-Electric Generators produce very low output voltages, which is insufficient for most low-power electronic circuits to operate. Therefore, a boost converter is essential to step up the voltage output from the TEG to a usable level. In this paper, a DC-DC converter with a high performance in terms of voltage gain is implemented. The proposed quasi-Z-source (q-ZSC) DC-DC converter not only offers high voltage gain but also several significant advantages. The proposed q-ZSC is capable of both boosting and regulating the voltage output efficiently, even under variable input conditions, making it highly suitable for low-power energy harvesting systems such as Thermo-Electric Generators. The design is simulated using MATLAB Simulink software, focusing on integrated circuits, with a strong emphasis on optimizing the circuit's efficiency. This work underscores critical factors in improving energy harvesting circuits, enhancing their performance and effectiveness in low-power applications for wearable technology. © 2024 The Authors.

关键词： DC generator motors

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A Deep Learning Approach for Faults Recognition of Dissolved Oxygen Sensor in Wastewater Treatment Plants 28

A Deep Learning Approach for Faults Recognition of Dissolved...

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28th IEEE International Conference on Emerging Technologies and Factory automation, ETFA 2023

作者： Ghinea, Liliana Maria Miron, Mihaela Ratnaweera, Harsha Electrical Engineering and Electronics Faculty of Automation Computers Department of Automatic Control and Electrical Engineering Department Galaţi Romania Computers Electrical Engineering and Electronics Faculty of Automation Department of Computer Science and Information Technology Galaţi Romania Norwegian University of Life Sciences Faculty of Science and Technology Oslo Norway

ISBN: (纸本)9798350339918

Fault diagnosis in wastewater treatment plants (WWTPs) is important to protect communities and ecosystems from toxic elements discharged into water. In this sense, fault identification of sensors plays an important role as they are the key components of the water plants control, especially because environmental legislation is very strict when referring to failures or anomalies in WWTPs. This paper analyzes the performances of two Deep Learning models, a Feedforward Neural Network (FFNN) and a 1D Convolution Neural Network (1DCNN) for identifying five operating states of the dissolved oxygen (DO) sensor: normal and faulty (bias, stuck, spike and precision degradation faults). The experiments were conducted on the Benchmark Simulator Model No 2 (BSM2) developed by the IWA Task Group. The performance of the Deep Learning (DL) classifiers was evaluated via accuracy, precision, recall, and F1-score metrics. The best overall classification accuracy was obtained by FFNN, 98.32% for training and 98.30% for testing. © 2023 IEEE.

关键词： Wastewater treatment

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A Sparse Quadratic Programming Approach to Supervisory control of Multi-Zone HVAC Systems with Consideration of Peak Demand Shaving and Thermal Comfort

A Sparse Quadratic Programming Approach to Supervisory Contr...

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International Conference on electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON

作者： Pasitnat Sasananand David Banjerdpongchai Department of Electrical Engineering Faculty of Engineering Center of Excellence in Intelligent Control Automation for Process Systems Chulalongkorn University Bangkok Thailand

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

The HVAC system is one of the major power consuming equipment in buildings. Considering the effective setpoint temperature of each zone can increase efficiency in managing power usage in buildings, leading to the operating cost reduction. This paper presents the design of supervisory control (SC) for multi-zone HVAC systems that aims to minimize the total operating cost (TOC) and the thermal comfort cost (TCC). To minimize the TOC and TCC, both objectives are normalized and combined as a quadratic programming (QP) problem which can be efficiently solved. To achieve the design objective, two methods of SC are developed for multi-zone, namely, centralized SC and decentralized SC. We apply standard QP and sparse QP solvers using interior point method. The numerical results reveal that centralized SC performs better according to a tradeoff curve which TOC and TCC are lower. While both solvers give the same results, sparse solver can provide the solutions faster than interior point method. This paper demonstrates that centralized control is appropriate for implementation in multi-zones buildings and the sparse solver proves to be more suitable in the context of sparse QP problem.

关键词： HVAC Costs Buildings Supervisory control Telecommunications Quadratic programming Sparse matrices

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Augmented Reality Application in Digital automation Laboratory

Augmented Reality Application in Digital Automation Laborato...

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2023 International Symposium on electrical and Electronics engineering, ISEE 2023

作者： Khang, Nguyen Trong Tran, Ngoc-Huy Phan, Nguyen-Phuc-Quoc VNU-HCM Faculty of Electrical & Electronics Engineering Department of Control & Automation Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350315486

Traditional automation engineering education using physical training equipment while quite effective, suffers from several limitations in the case there is no equipment access, which can be due to many reasons such as social distancing or financial difficulties. This article proposes a solution to overcome these limitations with the combinational use of mixed reality (MR), which helps the student get used to training equipment they have no access to, and augmented reality (AR), which brings intuitive visualization into real equipment practice. © 2023 IEEE.

关键词： Augmented reality

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Electrocardiogram Signal Secure Transmission via a Wireless Communication Protocol of Chaotic Systems Based on Adaptive Sliding Mode control and Disturbance Observer

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IEEE Access 2023年 11卷 145373-145385页

作者： Chien Le, Minh Giap, Van Nam Nguyen, Quang Dich Huang, Shyh-Chour Hanoi University of Science and Technology School of Electrical and Electronic Engineering Hanoi100000 Viet Nam Institute for Control Engineering and Automation Hanoi University of Science and Technology Hanoi100000 Viet Nam National Kaohsiung University of Science and Technology Department of Mechanical Engineering Kaohsiung807618 Taiwan

This paper presents a new application of the encryption and decryption techniques for securing the electrocardiogram (ECG) signal. The secure communication system (SCS) is embedded two Chen chaotic systems with different initial conditions, which were named master and slave, respectively. An ECG signal is encrypted by using master chaotic system. Which can be sent to the far destination to serving the heath care monitoring process. To obtain the original data, the state of the slave system is used to decrypt the signal. To obtain the goal, the master and slave need to be synchronized. Therefore, to softening the calculation of synchronization control design, the Takagi-Sugeno fuzzy (TSF) was used to remodel the master and slave into the fuzzy format, which are consists of the sublinear systems and fuzzy outer membership functions. Second, the disturbance observer (DOB) was proposed on slave system, which is used to reject the parameters variations and disturbances during the transmission. Third, the sliding mode control (SMC) was designed to synchronize the master and slave systems. Fourth, the stability of SCS is proved based on the Lyapunov condition. Finally, the simulation by using MATLAB software on computer and experiment by using the WIFI microchip ESP8266 were provided to show the power of the proposed methods. © 2013 IEEE.

关键词： Time domain analysis

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Point Cloud Classification Using Content-Based Transformer via Clustering in Feature Space

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 231-239页

作者： Yahui Liu Bin Tian Yisheng Lv Lingxi Li Fei-Yue Wang the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190 IEEE the Transportation and Autonomous Systems Institute(TASI)and the Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University Indianapolis(IUPUI)Indianapolis 46202 USA

Recently, there have been some attempts of Transformer in 3D point cloud classification. In order to reduce computations, most existing methods focus on local spatial attention,but ignore their content and fail to establish relationships between distant but relevant points. To overcome the limitation of local spatial attention, we propose a point content-based Transformer architecture, called PointConT for short. It exploits the locality of points in the feature space(content-based), which clusters the sampled points with similar features into the same class and computes the self-attention within each class, thus enabling an effective trade-off between capturing long-range dependencies and computational complexity. We further introduce an inception feature aggregator for point cloud classification, which uses parallel structures to aggregate high-frequency and low-frequency information in each branch separately. Extensive experiments show that our PointConT model achieves a remarkable performance on point cloud shape classification. Especially, our method exhibits 90.3% Top-1 accuracy on the hardest setting of ScanObjectN N. Source code of this paper is available at https://***/yahuiliu99/PointC onT.

关键词： Content-based Transformer deep learning feature aggregator local attention point cloud classification

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Multi-objective Optimal Operation of Centralized Battery Swap Charging System with Photovoltaic

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Journal of Modern Power Systems and Clean Energy 2022年第1期10卷 149-162页

作者： Yuanzheng Li Yihan Cai Tianyang Zhao Yun Liu Jian Wang Lei Wu Yong Zhao School of Artificial Intelligence and Automation Ministry of Education Key Laboratory of Image Processing and Intelligence ControlHuazhong University of Science and TechnologyWuhanChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingaporeSingapore College of Mechatronics and Control Engineering Shenzhen UniversityShenzhenChina Department of Electrical&Computer Engineering Stevens Institute of TechnologyHobokenUSA

Electric vehicles(EVs)are widely deployed throughout the world,and photovoltaic(PV)charging stations have emerged for satisfying the charging demands of EV *** paper proposes a multi-objective optimal operation method for the centralized battery swap charging system(CBSCS),in order to enhance the economic efficiency while reducing its adverse effects on power *** proposed method involves a multi-objective optimization scheduling model,which minimizes the total operation cost and smoothes load fluctuations,***,we modify a recently proposed multi-objective optimization algorithm of non-sorting genetic algorithm III(NSGA-III)for solving this scheduling ***,simulation studies verify the effectiveness of the proposed multi-objective operation method.

关键词： Multi-objective optimization electric vehicle battery swap charging system scheduling photovoltaic

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Texture Analysis of Breast US Images Using Morphological Transforms, Hausdorff Dimension and Bagging Ensemble Method 32

Texture Analysis of Breast US Images Using Morphological Tra...

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32nd Mediterranean Conference on control and automation, MED 2024

作者： Tabacaru, Gigi Moldovanu, Simona Barbu, Marian 'Dunarea de Jos' University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Automatic Control and Electrical Engineering Romania 'Dunarea de Jos' University of Galati Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Romania Dunarea de Jos University of Galati The Modelling & Simulation Laboratory Galati800008 Romania

ISBN: (纸本)9798350395440

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer. © 2024 IEEE.

关键词： Fractal dimension

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