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Optimal Design of Passive Filters for Minimization of Harmonic Distortion in Industrial Power System applications 13

Optimal Design of Passive Filters for Minimization of Harmon...

引用

13th International conference on Power Electronics, Machines and Drives, PEMD 2024

作者： Almutairi, Mohammed S. Saudi Arabia Ministry of Defense Riyadh Saudi Arabia

Harmonic distortion is a serious issue for both industrial customers and power suppliers. Therefore, its reduction is a basic requirement for any power system, to improve stability while complying with acceptable harmonic limits. An optimization method is presented which determines the compensatory values of an optimal passive filter, one which mitigates the harmonic pollution levels of frequency-dependent components in a non-sinusoidal power system, with the objective of maintaining the power factor within desired limits. The objective of the proposed method is to minimize the nonlinear current conditions of industrial customer's loads and the background voltage distortion from power suppliers at the point of common coupling (PCC). To further enhance the power quality performance, other practical constraints for the total voltage harmonic distortion limits are taken into account in the proposed design, ensuring compliance with ieee 519-2014 guidance and capacitor loading constraints established in ieee 18-2012. In addition, the harmonic resonance constraint is formulated to diminishing harmonic resonance risks that may arise from the passive filter connection. The utilization of shunt passive filters is the most widespread method of harmonic mitigation, due to their simplicity, practicality and ease of operational control Detailed results are provided which validate the performance of the passive filter according to widely used ieee standards assessments, based on previously published numerical examples of loads in non-sinusoidal conditions. © The Institution of Engineering & technology 2024.

关键词： Harmonic distortion

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Synergetic Innovation in Gherkin Cultivation Based on Machine Learning Algorithms

Synergetic Innovation in Gherkin Cultivation Based on Machin...

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2024 International conference on Computer and applications, ICCA 2024

作者： Jinasena, H.D.S.S. Dayarathna, T.W.K.D.A. Perera, H.M.A.G. Nissanka, K.G.T.R.K. Kasthurirathna, D. Gunathilake, M.P. Sri Lanka Institute of Information Technology Department of Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Sri Lanka

ISBN: (数字)9798350367560

ISBN: (纸本)9798350367560

Gherkin cultivation, while a significant contributor to the agricultural sector, remained underutilized in Sri Lanka despite high international demand, particularly for pickles. Gherkin farmers faced many challenges from pests, diseases, and unpredictable harvests. The main reasons identified were farmers' lack of knowledge, different weather conditions, and inability to identify the danger. The proposed system harnesses cutting-edge machine learning algorithms, computer vision, and object detection to address key challenges in Gherkin production. The solution enabled pest identification and control, disease diagnosis, and accurate harvest estimation addressing the utilization of gherkin cultivation in Sri Lanka despite high international demand, especially for pickles. By leveraging YOLOv8, Random Forest, and CNN architectures, the system returned reliable predictions and recommendations for the farmers. The unique approach of this research lies in its capability to deliver high-accuracy predictions, practical recommendations provide quick solutions for pest and disease problems that arise during cultivation and give an overview of the yield at the start of cultivation to the farmers. The innovations presented not only address the progression of Gherkin cultivation but also establish a foundation for future smart agriculture advancements. © 2024 ieee.

关键词： Adversarial machine learning

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A comparative analysis of using Deep Learning and Machine Learning technologies for intrusion detection for effective network traffic analysis 7

A comparative analysis of using Deep Learning and Machine Le...

引用

7th International conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Divya, S.B. Mary, S. Prince Department of Computer Science and Engineering Sathyabhama Institute of Science & Technology Chennai India Mangalam College of Engineering Department of Computer Applications India

ISBN: (纸本)9798350372816

The broad utilization of interconnectivity and interoperability of processing frameworks have turned into an irreplaceable need to improve our everyday activities. All the while, it opens a way to exploitable weaknesses that work out positively past human control capacity. The weaknesses consider network protection instruments fundamental to accepting correspondence trade. Secure correspondence requires safety efforts to battle the dangers and necessities headways to safety efforts that counter advancing security dangers. So, emerging technologies like Deep Learning/ Machine Learning (DL/ML) come in handy for integration and better prediction. So, in this paper, we depict various deep learning/ML strategies used in detecting the imbalance in network traffic. The document also includes research that has been proposed on the topic of intrusion detection in network traffic over the previous four years (2020-2024) by a variety of research specialists. The main achievements of the security measures are recognized in this review together with their quantitative and qualitative success indicators. Additionally, as a guide for upcoming discoveries, this research study examines the major discoveries and the rationale for the lessons discovered. © 2024 ieee.

关键词： Network intrusion

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Real-time Air Conditioning Unit Monitoring System with Analytics for Predictive Maintenance

Real-time Air Conditioning Unit Monitoring System with Analy...

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2024 ieee Region 10 conference, TENCON 2024

作者： Falcunitin, Jhon Michael Marcelino, C. Labayo Roxas, Ma. Arabela C. Titular, Lyka Eunice A. Santos, Adonis S. Malabanan, Francis A. College of Engineering First Asia Institute of Technology and Humanities Batangas Tanauan City Philippines

ISBN: (纸本)9798350350821

With the increasing reliance on air conditioning systems for indoor comfort and climate control, innovative approaches are imperative to enhance efficiency, reduce costs, and extend equipment lifespan. This study presents a comprehensive investigation into a real-time air conditioning unit monitoring system integrated with advanced analytics for predictive maintenance. Using wireless sensor networks and different learning algorithms, the advanced system is capable of collecting real-time data, including temperature, vibration, voltage and current flow from air conditioning (AC) units. It addresses problems in monitoring and performing maintenance late or excessively early in AC units. In the study, a comprehensive look at different predictive analytical algorithms is carefully identified and evaluated. The result is a system with a graphical user interface for displaying current value parameters and predictive insights. By combining these technologies, maintenance is kept to a minimum, the life of the equipment is lengthened, and continuity is ensured. This feature will significantly lessen the delay and hassle in manual monitoring of AC units in FAITH Colleges and other schools and establishments where the system may be deemed applicable and necessary. The integration of real-time monitoring with predictive analytics sets a new benchmark for AC unit maintenance, pushing the frontier of smart home and industrial applications. © 2024 ieee.

关键词： Graphical user interfaces

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Research on Constant Voltage Frequency Ratio control of AC Asynchronous Motor Based on DSP 4

Research on Constant Voltage Frequency Ratio Control of AC A...

引用

4th International conference on Advances in Electrical Engineering and Computer applications, AEECA 2023

作者： Shi, Shuqi Ren, Long Lin, Li Shaoyang University Hunan Provincial Key Laboratory of Grids Operation and Control On Multi-Power Sources Area Shaoyang China Central South University School of Automation Changsha China

ISBN: (纸本)9798350308082

In this paper, TMS320F2812 type DSP is utilized as the core of system control chip, according to the principle of variable voltage variable frequency (VVVF) and sine wave pulse width modulation technology(SPWM), thus the start accelerating of three-phase asynchronous motors is successfully achieved. In order to simplify the structure of the system and reduce the cost of the entire device, the main system circuit adopted the construction AC-DC-AC, constituting three-phase bridge rectifier by a power diode(SR) and three-phase inverter bridge by an insulated gate bipolar transistor(IGBT). By changing the output voltage and frequency of main circuit, the constant voltage frequency ratio control of three-phase asynchronous motor can be achieved. The experimental results verify the correctness and feasibility of the proposed scheme. © 2023 ieee.

关键词： Induction motors

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Estimation of Respiratory Rate Using Thermography 5

Estimation of Respiratory Rate Using Thermography

引用

5th International conference on Circuits, control, Communication and Computing, I4C 2024

作者： Alva, Rashmi Talasila, Viswanath Sushma, T.V. Umar, S A Raafay M.S. Ramaiah Institute of Technology Center for Imaging Technologies Bangalore India M.S. Ramaiah Institute of Technology Department of Electronics and TeleCommunication Engineering Bangalore India C M R Institute of Technology Department of Electronics & Communication Bangalore India

ISBN: (纸本)9798331528539

This study explores the application of infrared thermography for non-contact monitoring of human respiratory rate. Using a passive thermography approach, the study presents a non-invasive method utilizing thermal images, enabling continuous and remote respiratory rate monitoring without radiation exposure. Thermography's ability to detect changes in respiratory rate patterns can indicate various health conditions, often capturing early signs before clinical manifestation. Additionally, in driver monitoring systems, integrating low-level bio vitals like heart rate and respiratory rate with visual cues from cameras enhances road safety by enabling early detection of drowsiness. The study highlights various respiratory rate measurement methods, and its proposed methodology involves collecting data from healthy subjects using a handheld thermal imaging camera, processing thermal images to detect the nose region, and analysing temperature variations to derive respiratory rate signals. Validation against accelerometer data demonstrates promising accuracy, offering potential clinical applications as a non-invasive and accurate respiratory rate monitoring approach. © 2024 ieee.

关键词： Noninvasive medical procedures

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Broad Beamforming technology In 5G Massive MIMO

Broad Beamforming Technology In 5G Massive MIMO

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2024 International conference on Integration of Emerging Technologies for the Digital World, ICIETDW 2024

作者： Deepthi, K. Swetha, K. Venkareddy, M. Charan, G. Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering and Technology Dept. of ECE Hyderabad India

ISBN: (纸本)9798331541170

Massive MIMO (multiple input multiple output) technology plays a key role in many 5G networks today, boosting throughput and capacity by enabling user-specific beamforming of the data channel. For applications that require broad beams for large antenna arrays - broadcast and control signaling. Broad beamforming is a key component of 5G Massive MIMO, as it enables efficient and reliable communication with a large number of user devices in a variety of scenarios. It helps 5G networks deliver better coverage and capacity, especially in dynamic and challenging environments, making it a critical technology for the deployment of 5G services. Broad beamforming aims to create wider beams that cover a larger area and may not require as precise alignment. Combining broad beamforming technology with the Dual Polarized Beamforming (DPBF) technique in 5G Massive MIMO systems offers a powerful solution for adapting to changing user positions and channel conditions in dynamic environments. This approach provides flexibility in steering beams in both horizontal and vertical directions, improving the coverage and adaptability of the network. It's especially valuable in scenarios where user devices have varying polarization characteristics or when interference management is critical for optimal performance. © 2024 ieee.

关键词： 5G mobile communication systems

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Rotor Flux Estimation for Induction Motors Based on Modified Sliding Mode Observer 16

Rotor Flux Estimation for Induction Motors Based on Modified...

引用

16th International Symposium on Electronics and Telecommunications, ISETC 2024

作者： Wang, Yuheng Ionel, Raul Meng, Fanwei Li, Chunling Luo, Zhenzhong North China University of Science and Technology Electrical Engineering and Automation Department Hebei Tangshan China Politehnica University Timişoara Measurements and Optical Electronics Department Timişoara Romania

ISBN: (纸本)9798350390865

This paper presents a method for rotor flux estimation with direct applications in the control of induction motors (IM). We propose a new structure for the sliding mode observer (SMO) such that pure integral calculation for flux estimation is avoided. Simulation results, analyzed against performances of conventional SMOs, demonstrate that the proposed observer can directly estimate the rotor flux, and it is robust to parameter variations and load disturbance. © 2024 ieee.

关键词： Induction motors

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Multitask Learning for Multiple Recognition Tasks: A Framework for Lower-limb Exoskeleton Robot applications 32

Multitask Learning for Multiple Recognition Tasks: A Framewo...

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32nd ieee International conference on Robot and Human Interactive Communication (RO-MAN)

作者： Kim, Joonhyun Ha, Seongmin Shin, Dongbin Ham, Seoyeon Jang, Jaepil Kim, Wansoo Hanyang Univ Dept Appl Artificial Intelligence 55 Hanyangdaehak Ro Ansan Gyeonggi Do South Korea Hanyang Univ Dept Mech Engn Seoul South Korea Hexar Humancare Co Ltd Ansan South Korea Hanyang Univ Dept Interdisciplinary Robot Engn Syst Ansan South Korea Hanyang Univ ERICA Robot Dept Ansan Gyeonggi Do South Korea

ISBN: (纸本)9798350336702

To control the lower-limb exoskeleton robot effectively, it is essential to accurately recognize user status and environmental conditions. Previous studies have typically addressed these recognition challenges through independent models for each task, resulting in an inefficient model development process. In this study, we propose a Multitask learning approach that can address multiple recognition challenges simultaneously. This approach can enhance data efficiency by enabling knowledge sharing between each recognition model. We demonstrate the effectiveness of this approach using Gait phase recognition (GPR) and Terrain classification (TC) as examples, the most conventional recognition tasks in lower-limb exoskeleton robots. We first created a high-performing GPR model that achieved a Root mean square error (RMSE) value of 2.345 +/- 0.08 and then utilized its knowledge-sharing backbone feature network to learn a TC model with an extremely limited dataset. Using a limited dataset for the TC model allows us to validate the data efficiency of our proposed Multitask learning approach. We compared the accuracy of the proposed TC model against other TC baseline models. The proposed model achieved 99.5 +/- 0.044% accuracy with a limited dataset, outperforming other baseline models, demonstrating its effectiveness in terms of data efficiency. Future research will focus on extending the Multitask learning framework to encompass additional recognition tasks.

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Fault Recovery Method for Power Electronic Converters Based on Accelerator-Embedded Digital Twin 49

Fault Recovery Method for Power Electronic Converters Based ...

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49th Annual conference of the ieee Industrial Electronics Society, IECON 2023

作者： Sun, Jiaqin Buticchi, Giampaolo Li, Jing Zhang, He Guenter, Sandro Yang, Jiajun Province University of Nottingham Ningbo China Key Laboratory of More Electric Aircraft Technology of Zhejiang China

ISBN: (纸本)9798350331820

This paper presents a digital twin (DT)-based fault recovery method for power electronic converter systems. The method employs a prediction accelerator with a DT model for each subsystem of the converter system and feeds back the predicted system state to the controller. The paper demonstrates that the method can recover from faults such as load and input voltage variations in realtime and can integrate with hardware in the loop for future applications and comparing with other advanced control methods. The paper also highlights the benefits of the method in terms of scalability, replaceability and modularity for power electronic systems. © 2023 ieee.

关键词： Power converters

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