IEEJ Transactions on Electrical and Electronic Engineering最新文献_第3页

Ultraviolet Imaging of External Insulation Discharge of Electrical Equipment Based on Diffusion Model Detection 基于扩散模型检测的电气设备外绝缘放电紫外成像

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2025-01-10 DOI: 10.1002/tee.24267

Haili Gao, Jianzhong Hu, Wei Wu, Chao Tong, Min Li, Yufeng Zhuang

{"title":"Ultraviolet Imaging of External Insulation Discharge of Electrical Equipment Based on Diffusion Model Detection","authors":"Haili Gao, Jianzhong Hu, Wei Wu, Chao Tong, Min Li, Yufeng Zhuang","doi":"10.1002/tee.24267","DOIUrl":"https://doi.org/10.1002/tee.24267","url":null,"abstract":"An ultraviolet imaging method for the automatic detection of external insulation discharge in electrical equipment is proposed, based on a diffusion model. This study aims to enhance detection accuracy and efficiency by designing an anomaly detection framework that includes a training model, a fine-tuning model, and an inference model. By incorporating an unsupervised learning diffusion model, the method effectively addresses the issue of rare anomalies, achieving efficient and accurate anomaly detection and localization. Experimental results demonstrate that the proposed method excels in both image-level and pixel-level anomaly detection, significantly outperforming existing methods and providing reliable assurance for the safe operation of electrical equipment. This study highlights the practical significance of using deep learning models for automatic ultraviolet imaging detection, saving substantial manpower and resources. The method also offers the advantage of high sensitivity and a broad detection range, making it suitable for both day and night operations without interference from background light. Additionally, the implementation of a multi-level comparative analysis further improves the accuracy and reliability of anomaly detection, ensuring the effective identification and maintenance of potential issues in electrical equipment. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 7","pages":"1045-1055"},"PeriodicalIF":1.0,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development and Investigation of Novel High Torque Density Magnet Surrounded Permanent Magnet Synchronous Machine 新型高转矩密度永磁同步电机的研制

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2025-01-10 DOI: 10.1002/tee.24271

Long Yuhang, Song Zhanfeng

{"title":"Development and Investigation of Novel High Torque Density Magnet Surrounded Permanent Magnet Synchronous Machine","authors":"Long Yuhang, Song Zhanfeng","doi":"10.1002/tee.24271","DOIUrl":"https://doi.org/10.1002/tee.24271","url":null,"abstract":"A new high-torque density axial radial flux permanent magnet machine (ARFPMM) known as a magnet-surrounded permanent magnet synchronous machine (MSPMSM) is proposed. This machine combines toroidal winding with magnet-surrounding technology to create a three-sided effective air gap, reducing the winding's ineffective ends and improving torque density. The optimized design of the MSPMSM is focused on the magnetic concentrating ring, stator split ratio, winding configuration, and pole-arc coefficient. A detailed mechanical design is presented to prevent axial movement of the stator, and further strength analysis of the machine is conducted. The temperature rise and heat dissipation problems of the MSPMSM are more complex than those of conventional machines due to their compact structure and high torque density. Existing experience cannot accurately predict the heat generation of the machine, and modeling with the 3D finite element method (FEM) is complex and time-consuming. A fast lumped parameter thermal network (LPTN) method for MSPMSMs is proposed to address this issue. Finally, a prototype is fabricated and tested on a self-developed experimental bench to verify the high torque density of the proposed machine and the accuracy of the proposed LPTN method. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 7","pages":"1097-1106"},"PeriodicalIF":1.0,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Staged Multi-Strategy Framework With Open-Source Large Language Models for Natural Language to SQL Generation 基于开源大型语言模型的分阶段多策略框架，用于自然语言到SQL的生成

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2025-01-10 DOI: 10.1002/tee.24268

Chuanlong Liu, Wei Liao, Zhen Xu

{"title":"Staged Multi-Strategy Framework With Open-Source Large Language Models for Natural Language to SQL Generation","authors":"Chuanlong Liu, Wei Liao, Zhen Xu","doi":"10.1002/tee.24268","DOIUrl":"https://doi.org/10.1002/tee.24268","url":null,"abstract":"In the field of natural language to SQL (NL2SQL), significant progress has been made with large pre-trained language models. However, these models still have deficiencies in terms of their ability to generalize, particularly in open-source Large Language Models (LLMs). Additionally, most research efforts tend to overlook the impact of key column information and data table content on the accuracy of queries during the SQL statement generation process. In this paper, we propose a staged, multi-strategy framework called Key Columns and Table Contents (KCTC). The framework is divided into two stages. Firstly, it uses fixed prompt content to extract SQL key column information from natural language questions, including selected columns and conditioned columns. It also formats the output of column information. Secondly, it combines variable prompt content to guide the model in generating SQL statements. It uses the content of the data table for constraints to reduce the impact of errors in condition values on SQL statements. We conducted experiments on the Chinese dataset TableQA using several open-source LLMs. The results demonstrate that our method significantly improved the execution accuracy of SQL statements, with an average increase of 60.29% and reaching up to 91.22% accuracy. This result validates the effectiveness of our approach. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 7","pages":"1056-1065"},"PeriodicalIF":1.0,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning Approach to Energy Detection Based Spectrum Sensing for Cognitive Radio Networks 基于能量检测的认知无线电网络频谱感知的机器学习方法

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2025-01-10 DOI: 10.1002/tee.24261

Md. Tofail Ahmed, Mousumi Haque, Yosuke Sugiura, Tetsuya Shimamura

{"title":"Machine Learning Approach to Energy Detection Based Spectrum Sensing for Cognitive Radio Networks","authors":"Md. Tofail Ahmed, Mousumi Haque, Yosuke Sugiura, Tetsuya Shimamura","doi":"10.1002/tee.24261","DOIUrl":"https://doi.org/10.1002/tee.24261","url":null,"abstract":"Cognitive radio is an intelligent technology for wireless communication that optimizes the use of available frequency bands. Machine learning techniques can play an important role in spectrum sensing for cognitive radio networks to meet the rising traffic demand of wireless communication systems. The reliability of spectrum sensing methods depends on the prior knowledge of the noise to set a threshold. On the other hand, the success of a machine learning model relies on both the datasets and the accuracy of its learning algorithms. In this paper, we propose a spectrum sensing method for cognitive radio based on a machine learning algorithm in the conventional energy detection technique that removes the requirement to calculate the threshold. Initially, we introduce a method to build the dataset using the general concept of spectrum sensing based on the energy detection technique. The Naive Bayes supervised machine learning classification algorithm is implemented on the generated dataset for training, validation, and testing to sense the available spectrum. The proposed method is evaluated and tested using performance metrics such as confusion matrix, accuracy, precision, recall, F1 score, probability of detection, and probability of false alarm. In the simulation, the quadrature phase-shift keying (QPSK) modulation scheme over the additive white Gaussian noise (AWGN) channel is considered. The experimental outcomes of the proposed method provide satisfactory and acceptable performance for spectrum sensing in cognitive radio networks. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 6","pages":"910-919"},"PeriodicalIF":1.0,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144100644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-Objective Sleeve Optimization of Solid High Speed Permanent Magnet Motor Based on Rotor Strength Failure Judgment Parameters 基于转子强度失效判断参数的固态高速永磁电机套筒多目标优化

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2025-01-09 DOI: 10.1002/tee.24273

Zihao Yang, Baojun Ge, Chuanyou Dong, Dajun Tao, Zhifei Yang

{"title":"Multi-Objective Sleeve Optimization of Solid High Speed Permanent Magnet Motor Based on Rotor Strength Failure Judgment Parameters","authors":"Zihao Yang, Baojun Ge, Chuanyou Dong, Dajun Tao, Zhifei Yang","doi":"10.1002/tee.24273","DOIUrl":"https://doi.org/10.1002/tee.24273","url":null,"abstract":"It is necessary to consider the coupling effects of multiple physical fields in the rotor design of high speed permanent magnet motor. However, the calculation method ignoring axial constraints will lead to misjudgment of various strength failure modes of solid permanent magnet rotor. In this paper, the calculation methods of three kinds of judgment parameters of rotor strength failure modes under axial constraint are given by means of theoretical derivation. On this basis, a solid high speed permanent magnet motor of 38 000 rpm and 200 kW is taken as the research object to explore the rule of influence of sheath thickness on motor loss and temperature. Combining the rotor strength failure criterion and NSGAII algorithm, a new sleeve multi-objective optimization design method for solid high speed permanent magnet motor is proposed by taking the multi-physical properties such as strength, efficiency and temperature as objective functions. Finally, experiments and simulations are carried out to verify the effectiveness of the method. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 7","pages":"1118-1127"},"PeriodicalIF":1.0,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluation of Degradation Degree on Silicone Rubber by Using Surface Discharge 用表面放电法评价硅橡胶降解程度

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2025-01-07 DOI: 10.1002/tee.24256

May Thin Khaing, Nonoka Hirose, Takuma Miyake, Tatsuya Sakoda, Shigehiko Goto, Tomikazu Anjiki, Tomoki Chiba

{"title":"Evaluation of Degradation Degree on Silicone Rubber by Using Surface Discharge","authors":"May Thin Khaing, Nonoka Hirose, Takuma Miyake, Tatsuya Sakoda, Shigehiko Goto, Tomikazu Anjiki, Tomoki Chiba","doi":"10.1002/tee.24256","DOIUrl":"https://doi.org/10.1002/tee.24256","url":null,"abstract":"Silicone rubber (SiR) insulators in outdoor may be degraded owing to multiple environmental stresses such as ultraviolet (UV) rays, high temperature and pollution adhesion. Evaluation of the degradation degree of SiR can contribute to the long-term maintenance of SiR insulators. We proposed a novel technique to grasp the degradation degree of SiR. The surface discharge (SD) on the SiR surface temporarily decreased the surface hydrophobicity, and then the hydrophobicity recovery time was evaluated. The SD treatments were performed on SiR specimens cut out from unused, 10 and 20-year-aged SiR insulators, and the treatment time was from 5 to 25 s. After each SD treatment, the contact angle was evaluated at intervals of 10 min. As a result, it was found that the contact angle recovery time increases with the increase of SD treatment time. Also, the contact angle recovery times on 10 and 20-year-aged SiR specimens were longer than that on an unused SiR specimen, i.e. the contact angle recovery time after the SD treatment is useful for investigating the degradation degree. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 7","pages":"998-1005"},"PeriodicalIF":1.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Band Correlation-Based Multichannel Multiscale Convolution Network for Intelligent Interference Recognition 基于频带相关的多通道多尺度卷积网络智能干扰识别

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2024-12-17 DOI: 10.1002/tee.24226

Xiang Wang, Zining Zhao, Qi Wu, Haitao Xiao, Gang Li, Yibo Zhou, Wenjie Wang

{"title":"Band Correlation-Based Multichannel Multiscale Convolution Network for Intelligent Interference Recognition","authors":"Xiang Wang, Zining Zhao, Qi Wu, Haitao Xiao, Gang Li, Yibo Zhou, Wenjie Wang","doi":"10.1002/tee.24226","DOIUrl":"https://doi.org/10.1002/tee.24226","url":null,"abstract":"In recent years, with the development and extensive application of wireless communication technology, the communication system should have stronger anti-Jamming ability. Therefore, interference recognition is particularly important as a prerequisite for anti-interference. However, the existing traditional and intelligent interference recognition algorithms have problems such as complicated feature extraction and low recognition accuracy under low interference-to-noise ratio. In order to solve the above problems, this paper introduces parallel multi-channel multi-scale convolution to improve the speed and accuracy of network recognition. In addition, combined with frequency band correlation and long-short-term memory network (LSTM), an innovative wireless communication interference identification model based on frequency band correlation is proposed, which uses LSTM to detect the frequency band correlation of interference signals and improve the accuracy of interference identification under low Jamming noise ratio (JNR). Experiments prove that the model proposed in this article has faster recognition speed and better generalization. The introduction of frequency band correlation increases the recognition accuracy to more than 99% with low JNR. Therefore, the model proposed in this paper is an effective and available model in complex electromagnetic environments. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 5","pages":"736-748"},"PeriodicalIF":1.0,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detection and Classification of Surface Cracks Using Deep Learning Based Autoencoders in Eddy Current Testing 涡流检测中基于深度学习自编码器的表面裂纹检测与分类

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2024-12-16 DOI: 10.1002/tee.24243

Barrarat Fatima, Helifa Bachir, Bensaid Samir, Rayane Karim, Lefkaier IbnKhaldoun

{"title":"Detection and Classification of Surface Cracks Using Deep Learning Based Autoencoders in Eddy Current Testing","authors":"Barrarat Fatima, Helifa Bachir, Bensaid Samir, Rayane Karim, Lefkaier IbnKhaldoun","doi":"10.1002/tee.24243","DOIUrl":"https://doi.org/10.1002/tee.24243","url":null,"abstract":"Industrial equipment subjected to rigorous conditions of high speed and pressure leads to the development of cracks on metal surfaces. These cracks reduce the service life and threaten the safety of parts, and the deeper the crack, the greater the resulting damage. Crack detection and crack depth evaluation continue to take center stage in quantitative non-destructive testing and evaluation (NDT&E 4.0). The accuracy of the rotating uniform eddy current (RUEC) probe in achieving fast and efficient detection of surface cracks is corroborated by a comparison with previous experimental results. Next, accurate crack depth classification is achieved by building deep learning model based on a sparse autoencoder (SAE) and a multi-layer perceptron (MLP) model. These classifiers are combined with eddy current testing (ECT) data, including the normal magnetic component Bz. As a result, evaluation metrics such as accuracy increased by up to 100% with both precision and recall scores of 1 for the deep sparse autoencoder classifier compared to MLP performance. The originality of our approach is evident in the application of deep SAE, which achieves high classification accuracy. Furthermore, the integration of our high-resolution NDT&E RUEC probe with advanced machine learning models for depth classification is both novel and impactful. This unique combination offers a comprehensive framework for crack analysis, from precise detection to detailed characterization. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 5","pages":"676-687"},"PeriodicalIF":1.0,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Trends in High Voltage Switchgear Research and Technology 高压开关设备研究与技术的发展趋势

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2024-12-15 DOI: 10.1002/tee.24244

Martin Seeger, Felipe Macedo, Uwe Riechert, Markus Bujotzek, Arman Hassanpoor, Jürgen Häfner

{"title":"Trends in High Voltage Switchgear Research and Technology","authors":"Martin Seeger, Felipe Macedo, Uwe Riechert, Markus Bujotzek, Arman Hassanpoor, Jürgen Häfner","doi":"10.1002/tee.24244","DOIUrl":"https://doi.org/10.1002/tee.24244","url":null,"abstract":"High voltage switchgear is an essential element for the transformation of energy systems towards sustainable and low carbon footprint technologies by electrification of society and industry. This contribution highlights some important research and technology trends in high voltage (HV) switchgear development for reaching greener and smarter electricity transmission systems. In AC transmission, the focus is on the replacement of SF6, which is a strong greenhouse gas, in HV switchgear. Condition assessment is an important field within the “digitalization” of transmission systems to ensure reliability at reduced costs. Research activities and trends in these fields are discussed. Furthermore, HVDC transmission systems will be important for the future electricity system. As more point-to-point links are built, and as the need for HVDC transmission increases with a growing integration of renewables and rising demand for electricity, more complex multi-terminal HVDC grid topologies appear. Activities in this field are also presented with a focus on HVDC circuit-breakers and gas-insulated HVDC systems, which have been emerging in the last years. © 2024 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 3","pages":"322-338"},"PeriodicalIF":1.0,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/tee.24244","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143115070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

VMD-Based Feature Extraction and Enhanced GWO-DBN for Health Assessment of Automatic Transfer Switching Equipment 基于vmd的特征提取和增强的GWO-DBN用于自动交换设备健康评估

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2024-12-12 DOI: 10.1002/tee.24242

Guojin Liu, Yuze Yang, Daming Liu, Lekang Wang

{"title":"VMD-Based Feature Extraction and Enhanced GWO-DBN for Health Assessment of Automatic Transfer Switching Equipment","authors":"Guojin Liu, Yuze Yang, Daming Liu, Lekang Wang","doi":"10.1002/tee.24242","DOIUrl":"https://doi.org/10.1002/tee.24242","url":null,"abstract":"This article proposes a method for assessing the health condition of automatic transfer switching equipment (ATSE) during the switching process. The method combines variational mode decomposition (VMD) with deep belief networks (DBN) for non-invasive monitoring and fault diagnosis. First, the VMD method is introduced to address mode mixing, using sample entropy to determine the decomposition iterations of VMD. Wavelet packet energy entropy is then extracted as the feature for health condition assessment. Subsequently, the Gray Wolf Optimization (GWO) algorithm is enhanced with a nonlinear convergence factor and a dynamic weight strategy to improve performance and avoid local optima. The enhanced GWO is used to optimize the network parameters of the DBN, which then serves as the pattern recognition algorithm for assessing ATSE health. Comparative experimental analysis demonstrates that the proposed method effectively addresses the health condition assessment of ATSE vibration signals, exhibiting high diagnostic accuracy. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 5","pages":"801-811"},"PeriodicalIF":1.0,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0