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International Youth Scientific and Technical Conference on Relay Protection and Automation (RPA)

作者： A.V. Panashchatenko A.A. Yablokov Department of Electric Power Systems Automatic Control Ivanovo State Power Engineering University Ivanovo Russia

ISBN: (数字)9798331501105

ISBN: (纸本)9798331501112

Electromagnetic current transformers, invented more than 100 years ago, are today the most widespread type of preliminary current converters, used in organizing metrological channels for commercial and technical electricity metering, measuring and relay protection systems. Despite their relatively simple design and modest price, today the question of using unconventional preliminary current converters (Rogowski coils, optical transformers, galvanic-magnetic sensors) is being increasingly raised [1]. This situation is due to the shortcomings of electromagnetic current transformers (CT): large weight and dimensions), explosion and fire hazard, and also saturation of their magnetic conductor in transient modes with the presence of an aperiodic component in short circuiting (SC) current. The phenomenon of saturation leads to significant distortion of the transmitted secondary signal, which in turn may become the cause of overprotection with external SC or delayed protection with internal SC. Russian and international practice in coordinating CT characteristics and relay protection requirements presuppose ensuring correct operation of relay protection systems not only in steady, but also in transient modes with possible saturation of CT magnetic conductors [2]–[5]. At present, testing the correct operation of relay protection and automation devices (RPAD) in transient modes is carried out using the CT saturation time, which under the specific conditions of the location of the CT should be more than the exact current conversion time required for correct operation of the connected RPAD. This time is calculated by special approved methods [2]. Such use of two extreme CT magnetic conductor conditions (saturated/unsaturated), without regard to the current waveform itself may lead to significant inaccuracies in evaluating the correctness of RPAD operation. Fig 1 shows two instances of saturation in one and the same CT in different operating conditions and with the same time be

关键词： Current transformers Protective relaying Conductors Circuit faults Optical sensors Transient analysis Electromagnetics Saturation magnetization Fault currents Testing

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Optimization of Neural Networks using Swarm Intelligence Techniques for Achieving Energy Efficiency in Smart Building Architecture 1

Optimization of Neural Networks using Swarm Intelligence Tec...

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1st IEEE International Conference on Cognitive Robotics and Intelligent systems, ICC - ROBINS 2024

作者： Raja, M. Karthick Shermatova, Makhbuba Al Ansari, Mohammed Saleh Abdufattokhov, Shokhjakhon Rao, Vuda Sreenivasa Raj, I. Infant Sri Eshwar College of Engineering Department of Computer Science and Engineering Coimbatore India Turin Polytechnic University in Tashkent Civil Engineering and Architecture Department Tashkent Uzbekistan University of Bahrain College of Engineering Department of Chemical Engineering Bahrain Turin Polytechnic University Automatic Control and Computer Engineering Dept Italy Tashkent Intl. University of Education Dept of Information Technologies Tashkent Uzbekistan Koneru Lakshmaiah Education Fou. Green Fields Department of Computer Science and Engineering A.P Vaddeswaram522302 India K. Ramakrishnan College of Engineering Department of Computer Science and Engineering Tamil Nadu Trichy621 112 India

ISBN: (纸本)9798350372748

The increasing prevalence of smart building architectures, driven by the integration of Internet of Things (IoT) devices and automation systems, has led to a surge in energy consumption. This research explores the application of swarm intelligence techniques as an innovative approach to optimize neural networks, aiming to strike a balance between maintaining the desired performance levels and minimizing energy consumption. The study investigates the integration of swarm-based optimization algorithms, such as Particle Swarm Optimization (PSO) into the training and operation of neural networks. These algorithms enable the networks to dynamically adapt and optimize their parameters in response to changing environmental conditions and user requirements. The research focuses on developing a comprehensive framework that considers the specific challenges posed by smart building architectures, including real-time data processing, sensor integration, and adaptive control. The proposed approach aims to achieve optimal neural network configurations that minimize energy consumption while ensuring reliable and responsive operation of smart building systems. The results demonstrate the potential of swarm intelligence to significantly improve the energy efficiency of neural network-enabled smart building architectures, providing a promising avenue for sustainable and intelligent infrastructure. The proposed model has an accuracy of 98.23% which is 7.64% higher than that of the traditional approaches. © 2024 IEEE.

关键词： Energy efficiency

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Environment-Modulated Self-Assembly by Changes in Modules’ Buoyancy

Environment-Modulated Self-Assembly by Changes in Modules’ ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Xiao Chen Junyi Han Xin Jin Shuhei Miyashita Automatic Control and Systems Engineering Department University of Sheffield Sheffield UK Insigneo Institute for in Silico Medicine

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

While many inkjet printers employ only four types of ink (i.e. CKMY) to produce a wide range of colors, numerous technical challenges still exist for contemporary 3D printers to fabricate various materials and generate composite products such as electric devices. Conversely, there have been attempts and endeavors to make things through self-assembly of parts, analogous to the autonomous and decentralized development process of the human body from just 20 types of amino acids. In our previous work, we proposed a method for the rapid production of 3D objects using the centimeter-sized modules (referred to as Roblets) capable of generating a 2D structure and subsequently self-folding themselves into a 3D configuration, akin to origami. To further leverage the capability of generating a wide variety of different types of structures by combining different modules, this research studies a method of automatically selecting and supplying modules using environmental cues. More precisely, we developed a mechanism to couple different modules corresponding to three different environments (on a flat surface, on low-dense saline, and on saturated saline) and yielded different module configurations. The process of self-assembly necessitated the application of perturbation, which was realized by imparting magnetic torque originating from an external magnetic field onto the magnets embedded in the modules.

关键词： Self-assembly Three-dimensional displays Torque Buoyancy Production Magnetic fields Printers

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Assessment of the Digital Measuring Transformers Application in Power Distribution Zone

Assessment of the Digital Measuring Transformers Application...

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International Russian Automation Conference (RusAutoCon)

作者： Galina Filatova Vladimir Lebedev Andrey Tolstoukhov Automatic control of electric power systems department Ivanovo State Power Engineering University Ivanovo Russia

ISBN: (数字)9798350349818

ISBN: (纸本)9798350349825

Combined digital measuring current and voltage transformers (DCVTs), developed at Ivanovo State Power engineering University (ISPEU), are innovative products. The researchers have accumulated some operating experience of devices in existing electrical installations and experience in numerous laboratory tests. At the same time, a number of aspects of the DCVT use still remain the subject of research, for example, the functioning of DCVTs as a primary sensor for protection against single-phase ground faults (SPGFs). It is also necessary to evaluate the effect of the introduction of DCVTs in the overhead networks of power distribution zones (PDZs), primarily from the point of view of reducing the costs of searching for the location of the SPGFs. The procedure for searching for an electrical fault using the functions built into DCVT 6 -10 kV is described. The article describes the effects of the introduction of DCVTs in 6–10 kV distribution zones, and also provides criteria that allow us to assess in which cases the use of DCVTs and technologies based on them will be most beneficial.

关键词： Power measurement Costs Automation Electricity Power distribution Distribution networks Transformers Data models Circuit faults Integrated circuit modeling

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Processing Signals in Digital Current Measuring Transformers to Quickly Obtain the Vector for RPA Purposes

Processing Signals in Digital Current Measuring Transformers...

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International Conference on Industrial engineering, Applications and Manufacturing (ICIEAM)

作者： Vladimir D. Lebedev Denis G. Grigorev Nataliya V. Kuzmina Department of Electric Power Systems Automatic Control Ivanovo State Power Engineering University Ivanovo Russia

ISBN: (数字)9798350395013

ISBN: (纸本)9798350395020

In the development of secondary systems of stations and substations, including relay protection, automation, control, electric power metering and other features, there have recently been qualitative changes related to the introduction of digital technologies. The introduction of digital technologies is supported by innovative development programmes such as «Digital Transformation 2030». The essence of introducing digital technologies is related to the use of digital data transmission channels according to common standards. “Digital substation” projects are being actively implemented with transmission of digital information at all levels, starting with primary equipment, including transmission of information, both from current and voltage measuring transformers, and switchgear. Currently, digital measuring transformers are being actively developed and beginning to be introduced, in which information on measured current and voltage is presented in a digital code. New approaches to measuring primary current and voltage, and the transmission of information pose new challenges and open up new prospects of improving signals processing methods used for relay protection purposes. This determines the relevance of the objective of our research - developing and studying approaches to the digital processing of signals in digital current and voltage measuring transformers. As a result, the approach to determining synchronized values of current vectors was studied by processing information obtained from primary current converters. The characteristics of the algorithm for obtaining the vector were analyzed, and the dependences of errors on the influence of distorting factors were plotted. The proposed approach to obtaining the vector is a development of the existing approach by obtaining information from current sensors operating on different physical principles. The study shows the advantages of the proposed method.

关键词： Voltage measurement Substations Current measurement Signal processing algorithms Protective relaying Transformers Vectors

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Narrow gap TIG arc weld process monitoring 27

Narrow gap TIG arc weld process monitoring

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27th International Conference on Automation and Computing, ICAC 2022

作者： Gambrill, Nathan Farnsworth, Michael Shaw, Rob Tedeschi, Stefano Tiwari, Divya Tiwari, Ashutosh The University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom The Welding Institute Ltd Abington Cambridge United Kingdom

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

Joining processes play a critical role across several industries and manufacturing activities. One such activity is narrow gap TIG arc welding, present in a number of high value manufacturing domains the quality and outcomes are highly dependent on the operating parameters and the evolving state of the weld. Human supervision, and the application of vision systems to allow the operator to monitor the process as it is being undertaken is commonplace, however monitoring, characterisation and feedback in narrow gap use cases is less so. The work undertakes a comparative study into two different approaches to process monitoring of TIG arc welding. The first through more traditional machine vision (MV) methods, and the second through more modern deep neural network methods. Results show both methods developed are able to perform the role of process monitoring and defect detection with accuracy of 82% and 93% for the traditional and DNN methods respectively. © 2022 IEEE.

关键词： Deep neural networks

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Metaheuristic Optimization for Mobile Robot Navigation Based on Path Planning

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computers, Materials & Continua 2022年第11期73卷 2241-2255页

作者： El-Sayed M.El-kenawy Zeeshan Shafi Khan Abdelhameed Ibrahim Bandar Abdullah Aloyaydi Hesham Arafat Ali Ali E.Takieldeen Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Science Department College of Engineering and Computer ScienceMustaqbal UniversityBuraidahSaudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Mechanical Engineering Qassim UniversityBuraidah51452Saudi Arabia

Recently,the path planning problem may be considered one of the most interesting researched topics in autonomous *** is why finding a safe path in a cluttered environment for a mobile robot is a significant requisite.A promising route planning for mobile robots on one side saves time and,on the other side,reduces the wear and tear on the robot,saving the capital *** route planning methods for the mobile robot have been developed and *** to our best knowledge,no method offers an optimum solution among the existing *** Swarm Optimization(PSO),a numerical optimization method based on the mobility of virtual particles in a multidimensional space,is considered one of the best algorithms for route planning under constantly changing environmental *** the researchers,reactive methods are increasingly common and extensively used for the training of neural networks in order to have efficient route planning for mobile *** paper proposes a PSO Weighted Grey Wolf Optimization(PSOWGWO)*** is a hybrid algorithm based on enhanced Grey Wolf Optimization(GWO)with *** order to measure the statistical efficiency of the proposed algorithm,Wilcoxon rank-sum and ANOVA statistical tests are *** experimental results demonstrate a 25%to 45%enhancement in terms of Area Under Curve(AUC).Moreover,superior performance in terms of data size,path planning time,and accuracy is demonstrated over other state-of-the-art techniques.

关键词： Mobile robot swarm optimization robot route planning neural networks

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Evaluation of importance for condition attributes based on quality of decision reducts 26

Evaluation of importance for condition attributes based on q...

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26th International Conference on Knowledge-Based and Intelligent Information and engineering systems, KES 2022

作者： Stanczyk, Urszula Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

Relative or decision reducts belong with mechanisms dedicated to feature selection, and they are embedded in rough set approach to data processing. Algorithms for reduct construction typically aim at dimensionality reduction aspect, searching for smallest reducts, which are considered as the most advantageous from the point of view of knowledge representation. However, classifiers build on reduced data models, based on reducts, can significantly vary in performance. Therefore, to ensure quality of predictions, other characteristics of reducts, apart from their cardinalities, need to be taken into account. The paper presents research in which estimation of reduct quality through their characteristics was reflected in calculation of the proposed weighting factors leading to attribute rankings. These rankings were next employed in the process of filtering decision rules, inferred by classic rough set approach. Constructed rule-based classifiers were applied in the stylometric domain to solve a task of authorship attribution. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 26th International Conference on Knowledge-Based and Intelligent Information & engineering systems (KES 2022)

关键词： Rough set theory

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Toward quantum unmanned systems

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Science China(Technological Sciences) 2024年第7期67卷 2277-2280页

作者： CHENG ShuMing QI HongSheng SUN Yue LIU LiJun XIE ShaoRong REN XiaoQiang Department of Control Science and Engineering Tongji UniversityShanghai 200092China Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China Cipher Cloud Core Ltd. Beijing 100085China College of Mathematics and Computer Science Shanxi Normal UniversityLinfen 041081China School of Computer Engineering and Science Shanghai UniversityShanghai 200444China School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200444China

1 Quantum information technology Quantum information technology utilizes physical systems at the microscopic level, such as photon, atom, ion, and superconducting, to accomplish information-processing tasks that are impossible for the classical macroscopic world. During the past decade, significant process has been achieved in the pursuit of quantum technology into practical applications,generating great research interest from various domains, with the potential to radically change our information infrastructure [1–3].

关键词： quantum utilize generating

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Real-Time Object Detection and Robotic Manipulation for Agriculture Using a YOLO-Based Learning Approach 25

Real-Time Object Detection and Robotic Manipulation for Agri...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Zhao, Hongyu Tang, Zezhi Li, Zhenhong Dong, Yi Si, Yuancheng Lu, Mingyang Panoutsos, George Imperial College The Department Of Physics London United Kingdom University Of Sheffield The Department Of Automatic Control And Systems Engineering SheffieldS1 3JD United Kingdom University Of Manchester The Department Of Electrical And Electronic Engineering Manchester United Kingdom University Of Southampton The Department Of Electronics And Computer Science Southampton United Kingdom Fudan University The Department Of Economics Shanghai200433 China AmesIA50011 United States

ISBN: (纸本)9798350340266

The optimization of crop harvesting processes for commonly cultivated crops is of great importance in the aim of agricultural industrialization. Nowadays, the utilization of machine vision has enabled the automated identification of crops, leading to the enhancement of harvesting efficiency, but challenges still exist. This study presents a new framework that combines two separate architectures of Convolutional Neural Networks (CNNs) in order to simultaneously accomplish the tasks of crop detection and harvesting (robotic manipulation) inside a simulated environment. Crop images in the simulated environment are subjected to random rotations, cropping, brightness, and contrast adjustments to create augmented images for dataset generation. The You Only Look Once(YOLO) algorithmic framework is employed with traditional Rectangular Bounding Boxes (R-Bbox) for crop localization. The proposed method subsequently utilises the acquired image data via a visual geometry group model in order to reveal the grasping positions for the robotic manipulation. © 2024 IEEE.

关键词： Crops

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