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A Study on the Performance of Bearingless PMSM Based on Rotor Permanent Magnet Arrangement

Transactions of the Korean Institute of Electrical Engineers 2025年第4期74卷 739-746页

作者： Noh, Min-Soo Kim, Dong-Hyeon Guo, Youguang Lee, Ho-Joon Dept. of Electrical and Control Engineering Cheonju University Korea Republic of Dept. of Electronics and Electrical Engineering Dankook University Korea Republic of Dept. of Electronic Engineering Cheongju University Korea Republic of School of Electrical and Data Engineering University of Technology Sydney Australia

Magnetic bearing motors are in high demand due to their ability to operate in special environments without mechanical friction and lubrication, effectively avoiding wear and contamination. To overcome the complexity and maximum speed limitations, bearingless PMSMs (Permanent Magnet Synchronous Motors) have been developed. This study explains the electromagnetic driving principles of bearingless PMSMs based on generation conditions and the components of suspension forces. Furthermore, the permanent magnets arranged on the rotor are designed to alter the magnetic flux distribution using various magnetization patterns. FEA(Finite Element Analysis) was conducted for each model, and the derived results were compared and analyzed. This study investigates the performance of bearingless PMSMs based on different rotor permanent magnet arrangements, and draws a comprehensive conclusion. © The Korean Institute of Electrical Engineers.

关键词： Permanent magnets

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Detecting Cognitive Decline in Alzheimer's Disease using Brain Signals: An EEG Based Classification Approach 4

Detecting Cognitive Decline in Alzheimer's Disease using Bra...

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4th IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic control and Computer engineering, MI-STA 2024

作者： Mohammed, Asmaa Nasr College of Electronic Technology Dept. Control Engineering Bani Walid Libya

ISBN: (纸本)9798350372632

Alzheimer's disease is a long-term illness character-ized by a decline in abilities and the development of dementia. The main objective of this study is to explore the potential of using EEG-based classification for identifying and comprehending Alzheimer's disease in its stages. EEG, which measures brain ac-tivity, offers insights into the functioning of neurons. By applying machine learning techniques to EEG data, we have seen results in distinguishing between individuals with Alzheimer's disease and those without it. For our research, we used a dataset that included EEG recordings from individuals diagnosed with Alzheimer's disease, frontotemporal dementia, and healthy individuals for comparison. We extracted Mel coefficients (MFCC) as features and trained our models using decision trees and LightGBM classifiers. To evaluate their effectiveness, we assessed accuracy, sensitivity, specificity, and the area under the operating curve (AUC ROC). Our results showed accuracy in differentiating between Alzheimer's patients and healthy individuals, with an 89.3% accuracy rate along with AUC ROC values of 0.989 for the decision tree classifier and 98.64 % and 1.0 for the Igbm classifier, respectively. These findings highlight the potential of combining EEG-based classification with machine learning algorithms for diagnosis and personalized treatment planning for Alzheimer's disease. © 2024 IEEE.

关键词： Decision trees

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The Reconstruction of Seismic Reflection Events by Optimized Matching Pursuit Algorithm 6

The Reconstruction of Seismic Reflection Events by Optimized...

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6th International Conference on Intelligent control, Measurement and Signal Processing, ICMSP 2024

作者： Yu, Pingyang Liu, Yanping Wan, Defu Yao, Xue The College of Electronic Engineering Xi'an Shiyou University Dept. of Measurement and Control Technology and Instrument China

ISBN: (纸本)9798331516550

This paper mainly introduces an optimized matching pursuit algorithm for the reconstruction of seismic reflection events. It adopts intelligent optimization algorithms of genetic algorithm (GA) and particle swarm algorithm (PSO) to matching pursuit algorithm for improving the processing effect and efficiency. Through experiments on synthetic seismic records and field seismic data, it demonstrates that both GA-MP and PSO-MP can reconstruct the reflection events effectively and efficiency, while PSO-MP performs better especially in waveform reconstruction. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Unveiling Alzheimer's Disease Diagnosis with Convolutional Neural Networks: Visualizing Features and Class Activation Mapping 11

Unveiling Alzheimer's Disease Diagnosis with Convolutional N...

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11th IEEE International Conference on Systems and control, ICSC 2023

作者： Mohammed, Asmaa Nasr College of Electronic Technology Dept. Control Engineering Bani Walid Libya

ISBN: (纸本)9798350304886

This research paper explores the utilization of CNNs for diagnosing Alzheimer's disease, delving into techniques that enhance their interpretability and decision-making process. Feature visualization and class activation mapping provide insights into how CNNs detect the disease, emphasizing the importance of interpretability in medical imaging. The methodology involved skull stripping to isolate brain structures by removing non-brain tissues, followed by skull cropping to focus on the region of interest, improving the CNN model's accuracy and efficiency. Through training on the preprocessed dataset, the research achieved an impressive 99.92% accuracy in Alzheimer's disease detection, highlighting CNNs' potential for diagnosis. The study underscores the significance of understanding neural network decision-making, offering valuable insights into deep-learning models for medical imaging tasks. These findings contribute to improved Alzheimer's detection methods and enhance our understanding of applying deep-learning models in medical imaging, benefiting other diagnostic imaging tasks and advancing disease detection. © 2023 IEEE.

关键词： Visualization

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Development of control for Low Flow Application 4

Development of Control for Low Flow Application

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4th IEEE Asian Conference on Innovation in Technology, ASIANCON 2024

作者： Chikalthankar, Anagha N. Deshpande, Amruta S. Sonawane, Dayaram.N. Ghodinde, Ketaki A. Patil, Smita S. Coep Technological University Dept. of Instrumentation and Control Pune India Coep Technological University Dept. of Electronic and Telecommunication Engineering Pune India

ISBN: (纸本)9798350354218

Low-flow control applications are critical for shower systems and various industrial applications. These applications are indispensable due to the precise flow and temperature conditions required by many processes, which make them essential for achieving desired results. Present flow control applications vary in complexity, and some require skilled installation and maintenance, which can be expensive and sensitive. Traditional control methods can be limiting, resulting in heavy and bulky structures. This paper presents a novel mathematical modeling and advanced control strategy to control low flow applications. The presented simulation results, which include PID and fuzzy logic controllers, demonstrate that smooth control can be achieved by varying various parameters in combination. These findings offer valuable insights into the development of control strategies for low flow applications. © 2024 IEEE.

关键词： Three term control systems

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Detection of Consumer Electrical Load Profile Anomalies 20

Detection of Consumer Electrical Load Profile Anomalies

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20th International Conference on Smart Technologies, EUROCON 2023

作者： Farrugia, Michael Scerri, Kenneth Sammut, Andrew University of Malta Dept. of Systems and Control Engineering Msida Malta University of Malta Dept. of Electronic Systems Engineering Msida Malta

ISBN: (纸本)9781665463973

Faulty meters, billing inaccuracies and fraudulent activity all contribute to the non-technical losses experienced by power utilities. Apart from the intended advantage of billing efficiency, the advent of smart meters for consumption and load profile logging, has made possible the analysis of subscriber data for load balancing and consumer classification, amongst other uses. This study analyses data from smart meters in Malta and develops a method for anomaly detection aiming to identify costumers contributing to non-technical losses. Consumers are grouped into clusters with similar weekly consumption patterns using hierarchical clustering. For each consumer, two novel coefficients are then computed: the Anomaly Coefficient, which measures the divergence in consumption patterns for a consumer from all other member of the same cluster, and the Cluster Change Coefficient, which quantifies the likelihood of a customer to exhibit patterns associated with other clusters. Together these two measures are joined in a single Anomaly Score, thus identifying consumers with highly irregular consumption patterns. © 2023 IEEE.

关键词： Smart meters

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Criterion for Sufficiently Large Dither Amplitude to Mitigate Non-linear Glitches

Criterion for Sufficiently Large Dither Amplitude to Mitigat...

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2023 IEEE Conference on control Technology and Applications, CCTA 2023

作者： Faza, Ahmad Leth, John Eielsen, Arnfinn A. University of Stavanger Dept. of Energy and Petroleum Engineering Norway Aalborg University Dept. of Electronic Systems Automation & Control Denmark

ISBN: (纸本)9798350335446

A model describing glitch disturbances is introduced and analysed. The model is used to find the response of glitch disturbances when adding a periodic dither to the input and applying low-pass filtering to the output. This averaged response is used to find a criterion to determine a sufficiently large dither amplitude that will make the averaged glitch disturbances appear as a constant on the output of the low-pass filter. An important resulting property is that the averaged response to glitch disturbances is independent of the model input. By fitting the model to the measured response of a common off-the-shelf digital-to-analogue converter, simulations are used to verify the analytical results. © 2023 IEEE.

关键词： Low pass filters

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High-Fidelity Averaged Model of Grid-Following Inverter for Stability Analysis Considering the PLL Influence 32

High-Fidelity Averaged Model of Grid-Following Inverter for ...

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32nd IEEE International Symposium on Industrial electronics, ISIE 2023

作者： Goñi, Naiara Marcos, Javier Garcia, Miguel Garcia, Alberto Urtasun, Andoni Marroyo, Luis Nordex Acciona WindPower Dept. of Control Design Engineering Sarriguren31621 Spain Dept. of Electrical Electronic and Communications Engineering Campus de Arrosadía Pamplona31006 Spain

ISBN: (纸本)9798350399714

The grid share of renewable generation plants is increasing compared to conventional plants. The grid system is being affected by this transition, changing from a centralized synchronous generation to a distributed generation system where the grid connection is based on power inverters. Additionally, next-generation power networks are expected to be based on hybrid power plants consisting of different renewable plants working together, that is, different power inverters interconnected with each other. As maintaining secure operating conditions in the grid is a requirement, there is a pressing need to analyze the interaction between power inverters, which can lead to system instabilities. Therefore, this type of stability analysis requires models with a compromise in fidelity and computational cost. Power inverters have non-linear behaviour and thus, the existing literature focuses on two different implementations. Electromagnetic transient models (EMT) considering the switching components (SW), accurate models with a large computational cost, impractical for this type of analysis where a high number of inverters, parallelly coupled, are simulated. And, conversely, EMT averaged (AV) models with reduced simulation time but incapable of showing the stability limit of a real inverter due to the ideal implementation they are currently based on. However, this paper shows that AV models based on the fundamental control loops of a traditional grid-following (GFL) inverter free of idealizations, are representative of a real inverter when analyzing its stability, becoming a good choice to study multiple inverters interactions. © 2023 IEEE.

关键词： Electric inverters

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WIND FARM SENSOR FAULT DIAGNOSIS USING ARTIFICIAL INTELLIGENCE AND WAVELET TRANSFORM

WIND FARM SENSOR FAULT DIAGNOSIS USING ARTIFICIAL INTELLIGEN...

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International Conference on Green Energy, Computing and Intelligent Technology 2024, GEn-CITy 2024

作者： Aly, Mahmoud Shaaba, Mahmoud Kasem, Tamer Shalaby, Raafat Mechatronics Program Nile University Giza Egypt Nile University Giza Egypt Dept. of Engineering Mathematics and Physics Cairo University Giza Egypt Automatic Control Dept. Faculty of Electronic Engineering Menofia University Egypt

ISBN: (纸本)9781837242689

A methodology for the diagnosis of sensor faults in wind farms is introduced. Simulations are performed using a multi-domain model that integrates mechanical, electromagnetic, electronic control, and power grid components. The prevalent issue of intermittent sensor failures is addressed. The discrete wavelet transform is employed for feature extraction. The transient signals are processed effectively. Various wavelet families are evaluated to identify optimal candidates for fault diagnosis. Additionally, the methodology integrates three machine learning classifiers, achieving accuracy rates consistently exceeding 99%. The outcomes demonstrate the advantages of this approach in terms of enhanced accuracy. This research represents a significant advancement in sensor fault diagnosis, contributing valuable insights for the operation and maintenance of renewable energy systems. © The Institution of engineering & Technology 2024.

关键词： Windmill

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Further Studies of A Proof of Utkin's Theorem for ITSMC of Second Order Uncertain Plants

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Transactions of the Korean Institute of Electrical Engineers 2023年第10期72卷 1208-1220页

作者： Choi, Myeong-Soo Lee, Jung-Hoon Dept. of Control & Robot Engineering Gyeongsang National University Korea Republic of ERI Dept. of Control & Robot Engineering Gyeongsang National University Korea Republic of

In this paper, the two sliding surface part transformations are investigated for ITSMC (integral terminal sliding mode control) of second-order uncertain linear plants when the input gain uncertainty of the system is not zero i.e. ∆b≠0 as the further study of [33] and as the alternative methods of [33]. As highlighted in [33], the realm of designing ITSMCs encompasses five distinctive approaches: control input transformation, sliding surface full transformation, and three variations of sliding surface part transformations. While the discussion on the first three methods has been comprehensively covered in [33], this paper centers its focus on the previously unexplored last two transformations. These latter two transformations are presented as novel alternatives to the approaches detailed in [33]. The initial three transformations, as elucidated in [33], demonstrate a performance wherein the real output can be effectively predicted through the utilization of solutions derived from the ideal sliding dynamics. These solutions are thoughtfully pre-designed and predetermined through the application of the ideal sliding dynamics. This paper significantly contributes by presenting a comprehensive exploration of the last two transformation methods, achieving performance on par with the first three transformations described in [33]. These final two sliding surface part transformations stand as noteworthy design methodologies for ITSMCs with the same performance as in [33], offering alternative avenues in contrast to those laid out in [33]. The practical value of our key findings is effectively demonstrated through an illustrative example and an extensive simulation study, thereby underscoring the pertinence and applicability of our research outcomes. © The Korean Institute of Electrical Engineers.

关键词： Sliding mode control

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