IEEJ Transactions on Electrical and Electronic Engineering最新文献

Modeling Techniques for Light Distribution of White LEDs

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2025-02-16 DOI: 10.1002/tee.70000

Tomoaki Kashiwao, Kenji Ikeda, Masaru Tsumori, Kanji Bando

引用次数: 0

Classification Method for Fatigue Driving Signals Based on Multiple Classifier Analysis

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2025-01-23 DOI: 10.1002/tee.24260

Zhendong Mu

{"title":"Classification Method for Fatigue Driving Signals Based on Multiple Classifier Analysis","authors":"Zhendong Mu","doi":"10.1002/tee.24260","DOIUrl":"https://doi.org/10.1002/tee.24260","url":null,"abstract":"This study constructs an ensemble learning model under several classifiers by optimizing the hyperparameters of the base classifier to address the low accuracy issue of fatigue driving detection that uses traditional classifiers. In this study, the fatigue driving electroencephalogram (EEG) signals of 26 participants were analyzed using various classifiers, namely, k-nearest neighbor, back-propagation neural network, support vector machine, random forest, Gaussian naive Bayes, and quadratic discriminant analysis, as base classifiers. This study also used 10-fold cross-validation to evaluate the model and four ensemble learning methods, namely, bagging, boosting, stacking, and voting, for comparative analysis. Through the analysis of the EEG signals of the 26 participants, a conclusion could be drawn that the average recognition rate of the ensemble learning model for the participants was improved to 95% after hyperparameter optimization of the base classifier. Moreover, an ensemble learning model was constructed under multiple classifiers to improve the recognition rate of fatigue driving signals. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 4","pages":"647-655"},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143555120","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

Research on a Novel Online Obstacle Avoidance Algorithm in an Asymmetric Teleoperation

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2025-01-23 DOI: 10.1002/tee.24259

Hua Chen, Baoyu Shi

{"title":"Research on a Novel Online Obstacle Avoidance Algorithm in an Asymmetric Teleoperation","authors":"Hua Chen, Baoyu Shi","doi":"10.1002/tee.24259","DOIUrl":"https://doi.org/10.1002/tee.24259","url":null,"abstract":"Teleoperation robots are being used more and more widely. The safety issues of robots during operation are increasingly attracting people's attention; In actual dangerous environments, during the operation of the teleoperation control system, the real-time presence of obstacles com-presses the robot's safe workspace, leading to the failure of planned paths. This study is mainly about a robot online obstacle avoidance algorithm based on offline trajectory, aiming at the problems that ensure that the slave–robot is not affected during operation. Besides, this algorithm achieves the goal of avoiding obstacles by selecting obstacle avoidance parameters and allowing the robot to switch between primary and secondary movements in real-time. Two robot motion scenarios were selected in the article. One is obstacle avoidance with a single arm of slave–robot and the other is coordinated obstacle avoidance with a dual-arm robot for simulation experiments. The simulation experiment results showed that the algorithm proposed in this article is suitable for the designed asymmetric teleoperation system, the slave–robot can actively avoid obstacles under the control of the main robot. The algorithm perfectly satisfied the industry standards, and meet the design requirements of the teleoperation control system. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 4","pages":"656-664"},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143555121","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

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

Automotive Safety-Assisted Driving Technology Based on Computer Artificial Intelligence Environment

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2024-12-12 DOI: 10.1002/tee.24238

Haibo Yan

{"title":"Automotive Safety-Assisted Driving Technology Based on Computer Artificial Intelligence Environment","authors":"Haibo Yan","doi":"10.1002/tee.24238","DOIUrl":"https://doi.org/10.1002/tee.24238","url":null,"abstract":"A reasonable driving behavior decision model can choose the appropriate driving behavior according to the actual situation, thus improving the safety and efficiency of driving. To achieve an intelligent and humanized driving experience, this study explores the decision-making process behind driving behaviors. We have established a decision-making model for driving behaviors rooted in the finite state machine (FSM) paradigm. This model selects the most suitable driving action based on the car's current state, the surrounding environment, and the driver's intention. Given the intricate and varied nature of driving behaviors, we have incorporated a deep reinforcement learning (DRL) algorithm. This enables the optimization of decision-making strategies through dynamic interactions between the driver and the environment. Our findings reveal that this model adeptly handles complexities in real-world driving scenarios, thereby enhancing driving safety. In automotive contexts, FSM ensures the selection of apt driving actions aligned with the vehicle's status, environmental cues, and the driver's intentions. This innovative model surpasses traditional decision-making frameworks, paving the way for advancements in intelligent driving technology, and demonstrating remarkable adaptability and potential for further optimization. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 4","pages":"634-646"},"PeriodicalIF":1.0,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143555132","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

Grounding Grids Corrosion Evaluation of Electrified Railway Based on Two-Stage Optimization Algorithm

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2024-12-08 DOI: 10.1002/tee.24219

Minwu Chen, Yanyang Zhang, Jiadong Han, Yu Cao, Shuai Wang

{"title":"Grounding Grids Corrosion Evaluation of Electrified Railway Based on Two-Stage Optimization Algorithm","authors":"Minwu Chen, Yanyang Zhang, Jiadong Han, Yu Cao, Shuai Wang","doi":"10.1002/tee.24219","DOIUrl":"https://doi.org/10.1002/tee.24219","url":null,"abstract":"Due to the complex soil environment and continuous traction ground return, the electrified railway grounding grids (ERGG) are easily susceptible to corrosion, which seriously threatens the safe operation of the traction power supply system (TPSS). In this paper, the corrosion evaluation model is presented based on electrical network theory. In order to solve the equations with multi-variable and high-dimension characteristics of the model, a two-stage optimization (TSO) algorithm is proposed. In the first stage, the CPLEX solver (CPLEX optimizer produced by IBM) is adopted to obtain the resistance value of multiple branches, which provides the initial solver and search scope for the next step. In the second stage, the particle swarm optimization (PSO) algorithm is used to determine the optimal solution so as to minimize the node potential difference. Finally, a corrosion experimental system is designed and established to verify the effectiveness of the above algorithm. The results show that TSO algorithm can accurately diagnose the corrosion state of grounding conductors and adapt to the various scenarios of ERGG. © 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":"440-453"},"PeriodicalIF":1.0,"publicationDate":"2024-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112896","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

Aluminum Product Surface Defect Detection Method Based on Improved CenterNet

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2024-12-03 DOI: 10.1002/tee.24218

Zhihong Chen, Xuhong Huang, Ronghao Kang, Jianjun Huang, Junhan Peng

{"title":"Aluminum Product Surface Defect Detection Method Based on Improved CenterNet","authors":"Zhihong Chen, Xuhong Huang, Ronghao Kang, Jianjun Huang, Junhan Peng","doi":"10.1002/tee.24218","DOIUrl":"https://doi.org/10.1002/tee.24218","url":null,"abstract":"In order to realize real-time detection of aluminum defects during aluminum production, the target detection algorithm needs to be able to run on locally deployed hardware. Convolutional neural networks can effectively extract representative features from high-dimensional data such as images and videos, and capture spatial information in the data, making it easier to locate aluminum defects. Moreover, running CNN model inference on local hardware has high real-time performance. Due to the advantages of convolutional neural network in anomaly detection, an improved CenterNet aluminum surface defect detection method was proposed. The algorithm combines common convolution and depthwise separable convolution to design a lightweight convolution module. Then, the Convolutional Block Attention Module is added to the feature extraction network to make the network better capture the rich input feature information of the image. Ultimately, the α-DIoU loss function is implemented to enhance the precision of bounding box predictions. The experimental findings demonstrate that the proposed algorithm achieves an average detection accuracy (mAP) of 86.02%, which is 5.95% higher than the average detection accuracy of the traditional algorithm, and has a good detection effect on aluminum surface defects. Furthermore, there is an 11.9% reduction in model parameters and a 15.2% decrease in floating-point computations, which helps to promote the deployment of embedded device platforms. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 3","pages":"415-421"},"PeriodicalIF":1.0,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111132","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

Fourier Neural Network Circuit Implementation Based on Direct Weight Determination

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2024-11-28 DOI: 10.1002/tee.24230

Qinghui Hong, Zhenghan Guan, Jingru Sun, Sichun Du

引用次数: 0

Robust Dynamic State Estimation for Power System Based on Generalized Correntropy Loss Function and Unscented Kalman Filter

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2024-11-18 DOI: 10.1002/tee.24229

Tengpeng Chen, Hongxuan Luo, Yuhao Sun, Eddy Y. S. Foo, Tao Zeng, Gehan A. J. Amaratunga

引用次数: 0

IG-YOLOv8: Insulator Guardian Based on YOLO for Insulator Fault Detection

IF 1 4区工程技术

IEEJ Transactions on Electrical and Electronic Engineering Pub Date : 2024-11-06 DOI: 10.1002/tee.24221

Shenwang Li, Minjie Wang, Yuyang Zhou, Qiuren Su, Li Liu, Thomas Wu

{"title":"IG-YOLOv8: Insulator Guardian Based on YOLO for Insulator Fault Detection","authors":"Shenwang Li, Minjie Wang, Yuyang Zhou, Qiuren Su, Li Liu, Thomas Wu","doi":"10.1002/tee.24221","DOIUrl":"https://doi.org/10.1002/tee.24221","url":null,"abstract":"Insulators have an extremely important role in transmission lines, and they are important components for ensuring the safe operation of transmission lines. In order to solve the difficult problem of insulator fault detection under complex background, IG-YOLOv8 insulator fault detection algorithm is proposed in this paper. First, the Wise-IoU (WIoU) loss function is introduced to mitigate the adverse impact of low-quality images by employing a dynamic non-monotonic focusing mechanism, thereby enhancing the detection performance of the entire model. Second, a novel C2f network is constructed by integrating the receptive field coordination attention (RFCA) convolutional module to address the parameter-sharing issue associated with large convolutional kernels. Additionally, the data set has been reorganized using k-fold cross-validation to ensure that each subset undergoes training and testing, consequently reducing generalization errors. Finally, a deformable attention (DA) mechanism is employed to augment the feature extraction capability pertaining to insulator fault region information. In order to evaluate the detection performance of the improved IG-YOLOv8 algorithm, this study constructed an insulator target detection data set containing four fault types: Normal, Defect, Dirty, and Aging. The experimental results show that the average accuracy of the improved model is increased from 89.7% to 96.9%, and the Recall value of the Aging type insulator is increased from 71.8% to 89.1%. The occurrence of missed detection is greatly reduced, and the accuracy of detection is improved. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 4","pages":"537-547"},"PeriodicalIF":1.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143555097","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