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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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A Probabilistic Topology Inference Method for Networked Dynamical system via Single Excitation 63

A Probabilistic Topology Inference Method for Networked Dyna...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Jiao, Qing Li, Yushan He, Jianping Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Dept. of Automation Shanghai China

ISBN: (纸本)9798350316339

A growing number of works have investigated inferring the topology of networked dynamical systems from observations, such as to better understand the system behaviour. Despite the tremendous advances, most of them require the observations to be abundant. This paper focuses on inferring the topology by injecting single excitation on a node and collecting several steps of noisy observations. The problem is challenging because the noises cannot be depressed in several observations and are mixed with the injected excitation, making it hard to directly reveal the topology. To practice, we develop a probabilistic method based on the hypothesis test framework. First, we infer the neighbors that are within h-hop of the excited node and derive the accuracy guarantees. Then, we extend the method to infer the exact h-hop neighbors. A computable lower bound for the accuracy probability is established to provide confidence support in the inference procedures. Furthermore, we give the conditions of excitation input to ensure a desired inference probability, which provides guidance for the input design. Numerical simulations are conducted to verify the effectiveness of the proposed method. © 2024 IEEE.

关键词： Network topology

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control of Deterministic Chaotic Modes in Power systems

Control of Deterministic Chaotic Modes in Power Systems

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2023 IEEE International Conference on Smart Information systems and Technologies, SIST 2023

作者： Beisenbi, Mamyrbek Satpayeva, Ainur Mussabayeva, Shugla Mussina, Gulnara Tlegen, Meruert L.N. Gumilyov Eurasian National University Dept. of System Analysis and Control Astana Kazakhstan Astana It University Dept. of Computer Engineering Astana Kazakhstan

ISBN: (纸本)9798350335040

The paper examines a new approach to controlling deterministic dynamical chaotic mode of power system with two electric generate-sources. A control law is synthesized in the class of one-parameter structurally stable mappings from catastrophe theory. Analytical calculations and a numerical experiment in MatLab showed that the proposed system excludes the generation of a deterministic chaotic mode for any changes in the uncertain system parameters. The study of the control system is carried out by the gradient-velocity method Lyapunov vector functions © 2023 IEEE.

关键词： Uncertainty analysis

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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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A Study On Suitable Electrodes For Low-Energy Power Generation From Carbon Waste in Factories

A Study On Suitable Electrodes For Low-Energy Power Generati...

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2023 International Electrical engineering Congress, iEECON 2023

作者： Channgamthiang, Surasak Nusukhon, Pheeraphat Chansri, Pakpoom King Mongkut's University of Technology Thonburi Dept. Electrical Technology Education Bangkok Thailand King Mongkut's University of Technology Thonburi Dept. Control System and Instrumentation Engineering Bangkok Thailand

ISBN: (纸本)9798350332360

Factory waste includes the incomplete combustion of industrial fuels that causes carbon to precipitate in vents. These carbons might be put to good use. Therefore, the impact of using waste carbon in factories to produce electricity is investigated in this study by evaluating electrical characteristics: the type of electrode material's suitability, the size of the electrode's carbon contact surface area, and the distance between the electrodes. According to the findings, the maximum open circuit voltage (Voc) was 1.09 V for copper (+) and zinc (-) electrode materials, 1.11 V for the electrode's carbon contact surface area, and 1.29 V for the electrodes' spacing. The maximum of Voc was 1.11 V, maximum on-load voltage and current were 0.64V, 124.65 mA for optimum electrode carbon contact surface size 40 cm2. Optimum electrode distance at 2 cm that maximum open circuit voltage (Voc) was 1.29 V. The maximum load voltage and current were 0.77V, 128.32mA. Factory waste carbon can be useful in some applications for producing electricity from waste carbon and assisting in the reduction of factory waste. © 2023 IEEE.

关键词： Carbon

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Online PD Measurement by Detecting the Pulsed Compensating Current in High Voltage Equipment 8

Online PD Measurement by Detecting the Pulsed Compensating C...

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8th International Conference on engineering, Applied Sciences, and Technology, ICEAST 2022

作者： Srinangyam, Chissanupong Pannil, Pittaya Nimsanong, Phethai Chuayin, Chaitawat Thungsook, Kittisak Pattanadech, Norasage School of Engineering King Mongkut's Institute of Technology Ladkrabang Electrical Engineering Dept. Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Instrumentation and Control Engineering Dept. Bangkok Thailand Power System Operation and Control Section 2 Power System Control Dept. Metropolitan Electricity Authority Bangkok Thailand School of Engineering Rajamangala University of Technology Rattanakosin Electrical Engineering Dept. Bangkok Thailand

ISBN: (数字)9781665459198

ISBN: (纸本)9781665459198

This paper discusses the pulsed compensating current caused by partial discharge (PD) phenomena that flows inside the electrical equipment installed in the power system. Such electrical equipment like to be the capacitive coupler in the partial discharge test circuit. In order to study the pulsed compensating current of the PD measurement, artificial PD source such as corona, surface, and internal was used in this experiment. The electrical equipment like surge arrester combined with HFCT sensor utilized to detect the PD pulse current. Furthermore, this proposed technique has been applied for online PD measurement in substations. It was found that the surge arrester could compensate for the pulse current arising from the PD source. This study will be helpful information for online PD measurement. © 2022 IEEE.

关键词： Partial discharges

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Study on Deep Reinforcement Learning for Mobile Robots Flocking control in Certainty Situations 19

Study on Deep Reinforcement Learning for Mobile Robots Flock...

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19th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2022

作者： Kheawkhem, Pontakorn Khuankrue, Issarapong King Mongkut's University of Technology Thonburi Dept. of Control System and Instrumentation Engineering Bangkok Thailand

ISBN: (纸本)9781665485845

Mobile robots are the widely used machines that will be a part of life. It can easily be scaled to meet the requirements of human uses and can move to different target areas freely. However, mobile robots have a problem with mobility, which needs to respond to human activities and obstacles. Reinforcement learning (RT) is a part of machine learning, which enables the machine to learn by themselves. It can develop in a real-world environment without machine teaching or patterns. This paper proposed the study on the flocking control simulation, which avoids the obstacles. Mobile robots in simulation presented by using Multi-Agent Deep Deterministic Policy Gradient (MAD-DPG). The proposed algorithm, the deep reinforcement learning algorithm, is the main navigation of robots, which find the target, maintain distance between robots, and avoid collision with obstacles by learning features and characteristics with certainty environment, obstacle, robots, and target. On the simulation, the authors operate all of the positions in the environment, and robots speed in the environment as the state. © 2022 IEEE.

关键词： Reinforcement learning

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface 1

Optical Evanescent Field for Direct Observation of Sub-100nm...

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1st International Conference on Robotics, engineering, Science, and Technology, RESTCON 2024

作者： Khajornrungruang, Panart Permpatdechakul, Thitipat Suzuki, Keisuke Blattler, Aran Terayama, Yutaka Goto, Daiki Phaisalpanumas, Pipat Bun-Athuek, Natthaphon Phunopas, Amornphun Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Division Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Fukuoka Japan Kyushu Institute of Technology Iizuka-Shi Mechanical Information Science and Technology Division Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Production and Robotics Engineering Bangkok Thailand Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Course Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Industiral Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Bangsue College of Industrial Technology Dept. of Mechanical Engineering Technology Bangkok Thailand

ISBN: (纸本)9798350348842

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes. © 2024 IEEE.

关键词： Visualization

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