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检索条件"任意字段=International Conference on Electrical Engineering Computing Science and Automatic Control"

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Ensuring High Quality Power for Induction Motor Drive Through Thirty-Pulse Converter and Six-level 3P-2L-C5-VSI

Ensuring High Quality Power for Induction Motor Drive Throug...

引用

2023 IEEE international conference on Power Electronics, Smart Grid, and Renewable Energy, PESGRE 2023

作者： Kumar, Rohit Singh, Bhim Indian Institute of Technology Electrical Engineering Department Delhi India

ISBN: (纸本)9798350310573

High quality power through power converters for medium-voltage high-power industrial AC drive, is essential to enhance performance of the system, to reduce power losses and, thus, to improve the overall energy efficiency of the system. Multi-pulse and multi-level converters are the prominent solution for driving medium voltage induction motor (IM). This paper deals with a single unit of multi-winding transformer design with a phase displacement technique for a thirty-pulse power converter. This transformer has five-sets of three-phase secondary windings. This converter is utilized to ensure the quality of grid side current to adhere the power quality standard. Moreover, the DC voltages are generated through a 30-pulse converter, which are converted to AC voltages through a six-level 3P-2L-C5VSI converter. It is designed without any additional diode, bidirectional switches and floating capacitors. Although, the low frequency switching pulses for six-level 3P-2L-C5VSI are generated through a hybrid U-type and inverse U-type carrier waves-based modulation. Converter performance is ensured such that the quality of converter supplied motor currents meet the power quality standard. Simulation results are presented with closed-loop control to demonstrate high level of performance of medium voltage IM drive. © 2023 IEEE.

关键词： 3P-2L-C5VSI Phase Displacement Technique Power Quality Thirty-Pulse Converter U-Type and Inverse U-Type PWM

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Traffic Data Augmentation Using GANs for ITS

Traffic Data Augmentation Using GANs for ITS

引用

international conference on Distributed computing in Sensor Systems (DCOSS)

作者： Abdul Hamid Dabboussi Manar Jammal Electrical Engineering and Computer Science York University Toronto Canada School of Information Technology York University Toronto Canada

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

Intelligent Transportation Systems (ITS) play a pivotal role in shaping the foundation of smart cities, providing data-driven solutions for traffic management, prediction, and safety. However, these applications often face a significant challenge - data scarcity. Insufficient data limits the effectiveness of machine learning models in the context of ITS. To address this issue, this paper presents a novel data augmentation solution using Generative Adversarial Networks (GANs). By collecting sensor-based traffic speed data with contextual labels and training a GAN-based model to generate realistic traffic data for specific days and times, this research successfully proposes a solution to the problem of data scarcity. The generated data undergoes comprehensive qualitative and quantitative evaluations, demonstrating its potential to enhance ITS applications. Furthermore, the generated data is utilized to augment the training data for multiple traffic prediction models, effectively enhancing their performance. This approach opens new avenues for the development of intelligent and sustainable transportation systems, ultimately contributing to the advancement of smarter and more resilient cities.

关键词： Adaptation models Accuracy Computational modeling Transportation Training data Predictive models Traffic control

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Sliced Bidirectional Gated Recurrent Unit with Sparrow Search Optimizer for Detecting the Attacks in IoT Environment

Sliced Bidirectional Gated Recurrent Unit with Sparrow Searc...

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Distributed computing and electrical Circuits and Electronics (ICDCECE), IEEE international conference on

作者： Sureka R. Gondkar Siva Balan R V Kavitha S Raju Ramakrishna Gondkar Department of Electronic and Communication Engineering BMS Institute of Technology and Management Bangalore India Department of Computer Science CHRIST (Deemed-to-be-University) Bangalore India Department of MCA Nitte Meenakshi Institute of Technology Bangalore India

ISBN: (数字)9798350318609

ISBN: (纸本)9798350318616

In an era characterized by pervasive interconnectivity facilitated by the widespread adoption of Internet of Things (IoT) devices across diverse domains, novel cybersecurity challenges have emerged, underscoring the imperative for robust intrusion detection systems. Conventional security frameworks, constrained by their closed-system architecture, struggle to adapt to the dynamic threat landscape marked by the continual emergence of unprecedented attacks. This paper presents a methodology aimed at mitigating the open set recognition (OSR) challenge within IoT-specific Network Intrusion Detection Schemes (NIDS). Leveraging image-based representations of data, our approach focuses on extracting geographical traffic patterns. We observe that the Recurrent Neural Network exhibits suboptimal classification accuracy and lacks parallelizability for attack analysis tasks. Our investigation concludes that the Sparrow Search Optimization Algorithm (SSOA) serves as a foundation for constructing an effective assault classification model. This research contributes significantly to the field of network security by emphasizing the importance and ramifications of meticulous hyperparameter tuning. It represents a critical stride toward developing IDSs capable of effectively navigating the evolving cyber threat landscape. In the experimental analysis of proposed model reached the accuracy and 0.963% respectively.

关键词： Training Refining Logic gates Traffic control Search problems Internet of Things Task analysis

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Deep Q-Network based Tracking and Slope Climbing controller Design of Mobile Robot and Flatbed Vehicle

Deep Q-Network based Tracking and Slope Climbing Controller ...

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2021 international automatic control conference, CACS 2021

作者： Chou, Kuan-Yu Chen, Yu-Ting Ho, Shi-Lin Lin, Jing-Kai Chen, Yon-Ping Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University 1001 University Road Hsinchu Taiwan

ISBN: (纸本)9781665444125

Thanks to the technological change, the industry 4.0 has arrived. Artificial intelligence let software and machines to sense and learn on their own activities. In these research field, formation control of mobile robots is a popular topic. From rescue task to environment exploration, many of the applications require the robots to perform group patterns. To achieve these works, the control process could be simplified into multiple leader-follower relationships which control the followers to achieve the specific relative position with respect to the leaders. However, in particular situations, the tracking process should further consider the relative pose when both robots reach the desired relative position such as dynamic combination of robots. This paper proposes a Deep Q-Network based leader-follower tracking method with a climbing-up combination process. The control algorithm depends on the robot vision of the follower without any global measurements, and the whole process focuses on the relative pose between the mobile robot (follower) and the flatbed vehicle (leader). © 2021 IEEE

关键词： Mobile robots

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Multi-objective Dynamic Economic Dispatch 8th

Multi-objective Dynamic Economic Dispatch

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

作者： Yang, Wenqiang Zhu, Xinxin School of Mechanical and Electrical Engineering Henan Institute of Science and Technology Xinxiang 453003 Henan China

ISBN: (纸本)9789819602247

Power system's efficient operations and management heavily rely on dynamic economic dispatch (DED), which, due to its integration with spatial and temporal factors, poses a elaborate and intricate challenge in optimizing decision-making processes. The introduction of vehicle-to-grid (V2G) technology, which allows for the integration of plug-in electric vehicles (PEVs) to connect to the grid, serves as a viable solution to mitigate grid fluctuations and capitalize on the advantages of load leveling during peak times and utilizing off-peak electricity consumption. The paper introduces a model that incorporates current date, hourly dispatch of power systems as well as the influence exerted by Plug-in Electric Vehicles (PEVs). To resolve the model, an Osprey optimization algorithm (OOA) is introduced. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Vehicle-to-grid

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Cloud-Based IoT Solutions for Smart Grids: Advancing Smart Technologies in Energy Management

Cloud-Based IoT Solutions for Smart Grids: Advancing Smart T...

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international conference on electrical Power and Energy Systems (ICEPES)

作者： Franciskus Antonius Alijoyo Deepak A. Vidhate Chamandeep Kaur V Nivedan V. Kanpur Rani A. Balakumar School of Business and Information Technology STMIK LIKMI Bandung Indonesia Department of Information Technology Dr. Vithalrao Vikhe Patil College of Engineering Ahmednagar Maharashtra India Department of Computer Science Jazan University Jazan Saudi Arabia Department of Electronics and Communication System Sri Ramakrishna College of Arts & Science Coimbatore India Hindustan Institute of Technology and Science Chennai India Department of ECE K.Ramakrishnan College of Engineering Trichy India

ISBN: (数字)9798350390728

ISBN: (纸本)9798350390735

The incorporation of Internet of Things (IoT) cloud computing solutions with smart grids signifies a significant advancement in energy management. Traditional methods, though beneficial, often lack scalability and real-time capabilities, limiting their effectiveness in managing the complexity of modern energy systems. In this paper, a novel approach cloud-based IoT technologies to address these shortcomings and enhance smart grid functionalities. Existing energy management methods heavily rely on localized monitoring and control systems, constraining scalability and real-time responsiveness. Additionally, these methods struggle to handle the immense data generated by IoT devices dispersed throughout the grid. The proposed approach tackles these challenges by utilizing cloud computing to store, process, and analyze IoT sensor data in real-time. The novelty of this method lies in seamlessly integrating cloud-based platforms with IoT devices across the smart grid. Through utilising cloud resources, the limitations of traditional approaches are overcome, enabling scalable, real-time oversight and management of grid assets. The methodology involves deploying IoT sensors across the grid to compile information about energy usage, generation, and distribution, which is then transmitted to cloud servers for analysis and decision-making. Through simulations and real-world experiments, the effectiveness of this approach in optimizing grid performance, improving reliability, and facilitating demand-response programs is demonstrated. The results exhibit significant enhancements in grid efficiency and resilience, showcasing the potential of cloud-based IoT solutions to transform energy management in smart grids. Overall, this proposed method presents a promising pathway towards establishing more efficient, sustainable, and resilient energy infrastructure for the future.

关键词： Cloud computing Scalability Transforms Real-time systems Smart grids Internet of Things Servers

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Development of a Collaborative Hybrid Cyber-Physical Testbed for Analysing Cybersecurity Issues of DER Systems

Development of a Collaborative Hybrid Cyber-Physical Testbed...

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IEEE international conference on Smart Grid Communications (SmartGridComm)

作者： Ahmed S. Musleh Jawad Ahmed Nadeem Ahmed Hunter Xu Guo Chen Jiankun Hu Sanjay Jha Cyber Security Cooperative Research Centre (CSCRC) Perth Australia School of Electrical Engineering and Telecommunications University of New South Wales Sydney Australia School of Computer Science and Engineering University of New South Wales Sydney Australia School of Engineering and Information Technology University of New South Wales Canberra Australia

As renewable distributed energy resources (DER) become more integrated with power grids, maintaining a secure cyber infrastructure is essential for ensuring a sustainable and reliable power supply. This study examines various cyber-physical testbeds and research laboratories that have been established for developing and designing secure cyber-physical power system (CPPS), specifically DER systems. In addressing the limitations of existing testbeds, a new hybrid testbed is proposed that emphasizes vulnerability analysis of DER systems. The testbed combines simulation with real distribution network data, enabling researchers to study a range of cyberattacks and corresponding countermeasures. This testbed provides a platform for collaborative research and includes industrial components that allow for hardware-in-the-loop testing. Overall, the proposed testbed facilitates both qualitative and quantitative security risk assessments of different cyberattacks on the DER ecosystem. Case studies are provided to show the effectiveness of the developed testbed.

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Study on the Application of Tobacco Mechanical Optical Measuring 4

Study on the Application of Tobacco Mechanical Optical Measu...

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4th international conference on Robotics, Intelligent control and Artificial Intelligence, RICAI 2022

作者： Li, Junheng Wei, Xinfeng Yang, Guanglu Xu, Ruili Zhang, Dehai Li, Yanqin Huang, Zifan Mechanical and Electrical Engineering Institute Zhengzhou University of Light Industry Henan Zhengzhou China Nanyang Cigarette Factory China Tobacco Henan Industrial Co. Ltd Henan Nanyang China Henan Polytechnic Henan China

ISBN: (纸本)9781450398343

Optical measuring technology is widely used in the tobacco industry, not only for quality inspection of tobacco processing, but also for detecting defects in key mechanical components of tobacco processing equipment. Tobacco production requires the use of optical inspection technology to ensure quality. Optical precision measuring technology will therefore remain a research hotspot and focus in the future. In this paper, we first introduce the history of development and the characteristics of optical precision measurement technology. We then review the principle of measurement, key issues, and technical improvements over recent years in terms of structured light, binocular stereo vision, and digital speckle, as well as their applications in engineering. The calibration algorithm and measurement algorithm of structured light measurement technology need to be improved, and the optimization of the calibration technology and stereo matching technology of binocular stereo vision measurement needs to be improved urgently. How does the digital speckle correlation method adapt to a stronger measurement environment? Finally, we suggest a direction for further research that is worthy of further investigation based on the existing research. © 2022 ACM.

关键词： Speckle

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An IoT-Based Data Logging System to Ensure Consistent Dairy Product Quality Through Monitoring and Cloud Analytics 3

An IoT-Based Data Logging System to Ensure Consistent Dairy ...

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3rd international conference on Disruptive Technologies, ICDT 2025

作者： Malik, Praveen Kumar Keshari, Jaishanker Prasad Sethi, Gaurav Chauhan, Ashish Singh Yamsani, Nagendar Khera, Shelej School of Electronics and Electrical Engineering Lovely Professional University Punjab Phagwara India Government Engineering College Sheikhpura Bihar Engineering University Bihar Patna811105 India Uttaranchal University Uttarakhand Dehradun India School of Computer Science and Artificial Intelligence Sr University Warangal India

ISBN: (纸本)9798331519582

Pasteurization is intended to eliminate harmful microorganisms while maintaining the quality of milk and its other crucial constituents. As the consumption of dairy products increases in various regions across the globe, it becomes important to ensure that pasteurization is performed according to the set standards. Currently, the most major limitation of pasteurization processes is that they are overly dependent on the manual supervision and control. Besides the quality of the final product, this is a crucial factor for maintaining safety throughout. Furthermore, because they do not typically provide accurate data relating to the deviation of the process over a period of time. Nowadays having more of an automated solution, as well as computing capabilities of all systems in the cloud, has reduced redundancies across processes. In relation to the dairy sector, having those technologies enable efficiencies with respect to the precision, uniformity, and regulation of the entire pasteurization process. Consequently, the transfer to the automated systems undoubtedly improves operational performance as well as reduces errors related to the manual sanitation of the parameters particularly temperature and flow rate, which are critical and have to be maintained. Also, the factor of timely service is simplified because the machine is able to analyze data instantly, thus increasing productivity by reducing the downtime of operations. © 2025 IEEE.

关键词： Computer control

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The Algorithms of Recognizing Triple Junction and Extracting Angle for Grain Boundary Image 6th

The Algorithms of Recognizing Triple Junction and Extracting...

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6th international conference on computing, control, and Industrial engineering, CCIE 2021

作者： Dong, Yuehua Man, Jingjin Jiangxi University of Science and Technology Ganzhou341000 China

ISBN: (纸本)9789811939266

Aiming at the fact that the traditional electron back-scattered diffraction (EBSD) technique cannot directly obtain the parameters such as the angles of triple junction in the grain boundary image, the algorithm of recognizing triple junction based on convolution operation and the algorithm of extracting angle based on linear regression were proposed. Defined 16 different convolution kernels, respectively performed convolution operations on the image, and performed pixel-by-pixel judgment on the convolution result to identify the triple junction. Starting from the intersection of the triple junction, explored and recorded the coordinates of the triple junction, used linear regression to fit the triple junction, took points on the fitted line to construct triangle, and calculated the angles of triple junction according to the law of cosines. Experiments on the grain boundary image of B10 copper-nickel alloy show that the algorithms accuracy of recognizing triple junction and extracting angle are 100% and 96.9%, and the algorithms accuracy of counting the triple junction and angle distribution are 98.3% and 83.9%. The proposed algorithm effectively solves the problem that parameters such as the angles of triple junction in the grain boundary image cannot be obtained. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Grain boundaries

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