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Method of Classifying Motor Failure Conditions Using an Auto-Encoder-Based Ensemble Technique

Transactions of the Korean Institute of Electrical Engineers 2025年第2期74卷 273-279页

作者： Choi, Eui-Jin Han, Ji-Hoon Song, Seung-Min Park, Jong-Hoon Hong, Sun-Ki Dept. of System and Control Engineering Hoseo University Korea Republic of Dept. of Information Control Engineering Hoseo University Korea Republic of

In the field, unsupervised learning-based fault diagnosis is necessary due to the lack of fault data. However, conventional auto-encoder models face challenges in fault classification. To address this issue, this study proposes an unsupervised learning-based auto-encoder model enhanced with an ensemble approach. The proposed model performs fault classification using gear, bearing, and eccentricity fault data, and employs the Layer-wise Relevance Propagation (LRP) technique to improve fault classification. Through the LRP technique, the key frequency bands relevant to each fault are identified and incorporated into the learning process, allowing for frequency band-based training. As a result, the proposed auto-encoder model improves classification performance and effectively distinguishes between different types of faults. © The Korean Institute of Electrical Engineers.

关键词： Unsupervised learning

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Study on Improving Hysteresis Motor Efficiency by Over-Excitation Based on Finite Element Analysis

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Transactions of the Korean Institute of Electrical Engineers 2025年第1期74卷 49-55页

作者： Park, Jong-Hoon Han, Ji-Hoon Choi, Eui-Jin Hong, Sun-Ki Dept. of Information Control Engineering Hoseo University Korea Republic of Dept. of System and Control Engineering Hoseo University Korea Republic of

A hysteresis motor is a motor characterized by an increase in the efficiency of the output to input ratio during an over-excitation in which a higher voltage is applied at startup than when the rated voltage is applied, and the voltage is reduced over a period of time after entering synchronous speed. However, due to the specificity of the rotor material, finite element analysis of hysteresis motors is difficult, so the design was conducted by analyzing only the rated voltage application condition through an equivalent circuit. As a result, the improved efficiency and torque that can be achieved by over-excitation were not verified, which was confirmed by experiments after the design was completed. However, recently, finite element analysis simulation that can express the hysteresis loop behavior has become possible, so finite element analysis of hysteresis motors has become possible, and the improved efficiency and torque that can be obtained through over-excitation can be confirmed. Therefore, this paper compares the output and efficiency of hysteresis motors under over-excitation and rated voltage application, and confirms the necessity and feasibility of designing hysteresis motors considering over-excitation. Copyright © The Korean Institute of Electrical Engineers.

关键词： Equivalent circuits

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Performance Improvement of Transfer Learning-based Motor Fault Diagnosis Using Mix-up Data Considering Data Imbalance

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Transactions of the Korean Institute of Electrical Engineers 2023年第2期72卷 255-262页

作者： Choi, Eui-Jin Han, Ji-Hoon Hong, Sun-Ki Dept. of System and Control Engineering Hoseo University Korea Republic of Dept. of Information Control Engineering Hoseo University Korea Republic of

Most of the data obtained for motor fault diagnosis is the data of normal motors. Therefore, the model is trained using normal data collected in the field and fault data collected in experiment. In addtion, transfer learning is used for fast learning convergence. Fault diagnosis performance may be reduced by the number of unbalanced data in each state during transfer learning. In this study, a transfer learning method using mix-up data is proposed to solve this data imbalance. A mix-up is a technique of adding insufficient data to the data with clear decision boundaries, and can be used to balance a large number of normal state data with a small number of fault-state data. The proposed method is compared with GAN, another technique of data augmentation. As a result of the experiment, it was confirmed that the proposed mix-up technique is a method to improve the performance of fault diagnosis. Copyright © The Korean Institute of Electrical Engineers.

关键词： Failure analysis

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Performance Analysis of Transfer-Learning Based Physics-Informed Neural Network for Effective Shape Variation Adaptation with Varying Hyper-parameters

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Transactions of the Korean Institute of Electrical Engineers 2023年第10期72卷 1149-1158页

作者： Han, Ji-Hoon Choi, Eui-Jin Hong, Sun-Ki Dept. of System and Control Engineering Hoseo University Korea Republic of Dept. of Information Control Engineering Hoseo University Korea Republic of

One of the most time-consuming parts of designing an electrical device is optimizing the geometry. Optimization involves fine-tuning dimensions such as slot widths and airgap lengths from a base geometry to meet user needs. FEA(Finite Element Analysis) is typically used to verify this performance. However, conventional FEA requires a separate analysis if the analysis geometry is varied even slightly. This causes a very long time consumption, and a transfer learning-based PINN(Physics-Informed Neural Network) is proposed to solve this problem. Since PINNs are at the basic level worldwide, their performance is analyzed according to hyper-parameters such as model parameters (e.g. weights or biases), preprocessing methods, activation functions, and the number of training data to increase their performance. Based on the analyzed hyper-parameters, the performance of the transfer learning-based PINN is verified under the condition of varying the airgap length of the E-I core. © 2023 Korean Institute of Electrical Engineers. All rights reserved.

关键词： Geometry

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The Method of for Analyzing EMI Conducted Noise Analysis in Power Conversion Devices using Partial Element Equivalent Circuit Modeling

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Transactions of the Korean Institute of Electrical Engineers 2023年第7期72卷 809-819页

作者： Seo, Hyun-Woo Kim, Rae-Young Dept. of Electrical Engineering Hanyang University Korea Republic of Dept. of Energy Power Electronics Control System Lab Hanyang University Korea Republic of

EMI conducted noise is becoming increasingly important in power conversion systems, and various analysis methods are being researched. The proposed method enables accurate EMI conducted noise analysis by extracting partial element equivalent circuits from the 3D structure of power cables and PCBs, and the extracted model can be interpreted in SPICE simulations. The implemented inverter operation mode of Totem-Pole bridge-less PFC in the EMI conducted noise analysis simulation model shows a good correlation between simulation results and experimental results in all CE bands. Furthermore, this method identifies the main causes of EMI noise through CM (Common Mode) and DM (Differential Mode) noise analysis, and proposes a method to effectively attenuate EMI noise through CM coil modeling. Therefore, the EMI conduction noise analysis method using simulation models allows for efficient prediction of EMI conduction noise in advance. Copyright The Korean Institute of Electrical Engineers.

关键词： Poles

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Performance Evaluation of the Continuos Wavelt Transformation Data in Motor Fault Diagnosis through XAI Algorithm

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Transactions of the Korean Institute of Electrical Engineers 2022年第1期71卷 225-232页

作者： Han, Ji-Hoon Park, Sang-Uk Hong, Sun-Ki Dept. of Information Control Engineering Hoseo University Korea Republic of Dept. of System and Control Engineering Hoseo University Korea Republic of

The data mainly used for motor fault diagnosis is FFT. However, preprocessing such as continuous discrete wavelet transform is used. When using deep learning algorithms, the performance of the data is evaluated by the model output. However, in order to improve the learning possibilities and preprocessing performance of data, performance evaluation from a model perspective is required. For this purpose, data performance evaluation using the LRP algorithm, one of the XAI techniques, is studied. Initial fault state diagnosis using current data, which is difficult to solve with FFT data, is performed with STFT and CWT data, and performance is evaluated through LRP. Experimental Results STFT and CWT are preprocessing techniques that enable the use of current signals for early fault diagnosis. Among the two preprocessing methods, the use of CWT is more preferable because the flexibility of the preprocessing is increased. © 2022 Korean Institute of Electrical Engineers. All rights reserved.

关键词： Failure analysis

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Balancing Power in a Grid-Linked Inverter with an Unbalanced Grid Through Parallel Current control

Balancing Power in a Grid-Linked Inverter with an Unbalanced...

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2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2024

作者： Soth, Panha Choeung, Chivon San, Sokna Yay, Socheat Tang, Heng Torn, Vanna In, Sokvan Cheng, Horchhong Dept. of Control System National Polytechnic Institute of Cambodia Phnom Penh Cambodia Dept. of Control System NPIC Phnom Penh Cambodia Dept. of Electrical Installation NPIC Phnom Penh Cambodia Dept. of Gen. Transmisssion and Sub-Transmission EAC Phnom Penh Cambodia Faculty of Electricity NPIC Phnom Penh Cambodia

ISBN: (纸本)9798331533137

This paper presents an approach for power balancing in grid-linked inverters within the context of smart grids, addressing the challenge of unbalanced grid voltage conditions. The proposed method employs a paralleled current control strategy, utilizing state feedback integral control to regulate both positive and negative sequence currents. This approach ensures resilient performance under grid voltage imbalances, which are a common problem in smart grid environments. The control gains are optimized through a linear matrix inequality-based method, enhancing the system’s stability and responsiveness to fluctuating grid conditions. Simulations conducted using MATLAB and PSIM demonstrate the effectiveness of this control strategy in maintaining power balance and achieving a unity power factor despite unbalanced grid voltages. This study aims to contribute to the improvement of smart grid technologies by offering a dependable and efficient solution for power balancing in grid-connected inverter systems. ©2024 IEEE.

关键词： Smart power grids

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Comparison of Fast Frequency Response Methods in the Low-Inertia Grid of Cyprus 3

Comparison of Fast Frequency Response Methods in the Low-Ine...

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Argyrou, Andreas Panagi, Savvas Aristidou, Petros Electricity Authority of Cyprus Distribution System Operator Nicosia Cyprus Cyprus University of Technology Dept. of Electrical & Computer Engineering & Informatics Limassol Cyprus

ISBN: (纸本)9798350375923

Modern electric power systems with high levels of penetration of renewable energy sources (RES) often present frequency security problems. The lack of inertia due to the reduced number of synchronous generators in these systems, in combination with the usual inability of RES to provide frequency support, leads to system operators having to curtail RES or rely heavily on Under Frequency Load Shedding schemes to ensure frequency security. Fast Frequency Reserves (FFR) have been proposed as a solution to strengthen the frequency support of the system and alleviate security problems. FFR allows mitigating Rate of Change of Frequency, Nadir, and post-fault frequency steady-state problems after an event. In this paper, we present, analyze, implement and compare five FFR controllers to alleviate frequency security problems in low-inertia grids. The low-inertia, islanded, Cyprus dynamic model is used to quantify the results and exhibit the impact on a real system. © 2024 IEEE.

关键词： Synchronous generators

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NEW TOOL FOR system IDENTIFICATION AND PREDICTIVE control BASED ON NEURAL NETWORKS USING LABVIEW SOFTWARE

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2022年第2期84卷 91-110页

作者： Alshareefi, Hamid Lupu, Ciprian Alboudkhal, Hayder Ismail, Laith Dept. of Automatic Control and Computers University POLITEHNICA of Bucharest Romania Ministry of Electricity Iraq Dept. of Computer Technology Engineering AL-TURATH University College Baghdad Iraq

In this paper, a new tool for system identification and model predictive control (MPC) has been developed. The mathematical approximation of the model identification was derived using the neural network theory. The emphasis of this paper is to employ a multi-layer recurrent neural network with three layers to match an autoregressive-moving average (ARMA) model in the identification stage to provide the mathematical model for the model predictive controller in the control stage. The tool was designed using LabVIEW software and the MathScript facility. The tool can be used to identify and control simulated or real systems using the stored input/output data of the system. © 2022, Politechnica University of Bucharest. All rights reserved.

关键词： Recurrent neural networks

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A Dynamic Security Assessment Tool for Modern Power systems with Massive RES Penetration 3

A Dynamic Security Assessment Tool for Modern Power Systems ...

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Therapontos, Phivos Charalambous, Charalambos A. Aristidou, Petros Electricity Authority of Cyprus Distribution System Operator Nicosia Cyprus University of Cyprus Department of Electrical and Computer Engineering Nicosia Cyprus Cyprus University of Technology Dept. of Electrical & Computer Engineering & Informatics Limassol Cyprus

ISBN: (纸本)9798350375923

Modern power systems are facing significant challenges due to the massive penetration of renewable energy sources (RES). Recently, issues related to frequency security, system strength, and excessive fault levels have been experienced in some power systems. Classical dynamic security assessment (DSA) tools have not been developed to identify and analyze these new challenges that are critical in low-inertia grids. In this paper, a DSA tool has been developed that evaluates frequency security, system strength, and maximum fault levels to allow for secure system planning and operation. Furthermore, to increase the accuracy of the DSA tool, inverter-based resources' (IBRs') protections and capabilities have been incorporated in the DSA tool. A real-time operation and an operational planning application of the DSA tool are showcased using the islanded Cyprus Power system. © 2024 IEEE.

关键词： Dynamic security assessment frequency security IBR modeling low-inertia grids system strength

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