IEEJ Transactions on Electrical and Electronic Engineering最新文献

{"title":"Trends in High Voltage Switchgear Research and Technology","authors":"Martin Seeger,&nbsp;Felipe Macedo,&nbsp;Uwe Riechert,&nbsp;Markus Bujotzek,&nbsp;Arman Hassanpoor,&nbsp;Jürgen Häfner","doi":"10.1002/tee.24244","DOIUrl":"https://doi.org/10.1002/tee.24244","url":null,"abstract":"<p>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.</p>","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}

{"title":"VMD-Based Feature Extraction and Enhanced GWO-DBN for Health Assessment of Automatic Transfer Switching Equipment","authors":"Guojin Liu,&nbsp;Yuze Yang,&nbsp;Daming Liu,&nbsp;Lekang Wang","doi":"10.1002/tee.24242","DOIUrl":"https://doi.org/10.1002/tee.24242","url":null,"abstract":"<p>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.</p>","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}

{"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":"<p>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.</p>","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}

{"title":"Risk-Averse Distributionally Robust Environmental-Economic Dispatch Strategy Based on Renewable Energy Operation: A New Improved Whale Optimization Algorithm","authors":"Yubing Liu,&nbsp;Guangkuo Gao,&nbsp;Wenhui Zhao","doi":"10.1002/tee.24239","DOIUrl":"https://doi.org/10.1002/tee.24239","url":null,"abstract":"<p>Although the use of optimization techniques for environmental and economic dispatch of integrated electricity and natural gas systems has been widely applied, there are still significant challenges in meeting the multiple energy demands of conventional and renewable energy sources, mainly wind-solar. In this study, Wasserstein distance is introduced to measure the randomness of wind-solar power generation to construct the uncertainty set. A multi-objective distributionally robust optimization (MODRO) environmental-economic scheduling model for risk aversion that minimizes the risk cost, the system operation cost, and the carbon emission cost is proposed to achieve the balance between the risk cost, the operation cost, and the pollutant emission. To solve the model efficiently, the multi-objective whale optimization algorithm (IMOWOA) was improved and used the 4-node power system and the 7-node natural gas system as case studies. The results show that the MODRO environmental-economic scheduling model can measure the operational risk due to the stochastic fluctuation of wind-solar energy sources, and provide an effective decision-making tool for policymakers. Considering P2G technology and gas turbines at the same time, it promotes the coupled operation of electric-gas integrated systems and achieves good economic efficiency. Thus, the model provides an effective solution for the stability, economy, and cleanliness of the integrated electric gas system. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.</p>","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 5","pages":"696-711"},"PeriodicalIF":1.0,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749346","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}

{"title":"Device-Free Detection of Pedestrian and Movement Direction Using Bluetooth Direction Finding Function","authors":"Yoshiaki Taniguchi,&nbsp;Ren Imao,&nbsp;Nobukazu Iguchi","doi":"10.1002/tee.24253","DOIUrl":"https://doi.org/10.1002/tee.24253","url":null,"abstract":"<p>From Bluetooth 5.1, a direction finding function has been added that allows the receiver to measure the angle of arrival (AoA) of the wireless signal from the sender. In this letter, we propose a method for detecting pedestrians and their movement direction passing between Bluetooth devices equipped with direction finding functions. As a result of the evaluation, pedestrians could be detected with higher accuracy (F-score 0.929) by combining received signal strength indicator and AoA than when using each alone. In addition, the accuracy rate for estimating the movement direction using AoA was 0.704. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.</p>","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 6","pages":"969-971"},"PeriodicalIF":1.0,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144100483","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}

{"title":"Practical Trajectory Anonymization Method Using Latent Space Generalization","authors":"Yuiko Sakuma,&nbsp;Hiroaki Nishi","doi":"10.1002/tee.24254","DOIUrl":"https://doi.org/10.1002/tee.24254","url":null,"abstract":"<p>The global positioning system (GPS) data are commonly used for location-based services such as traffic flow prediction. However, such data contain considerable sensitive information and thus, they must be anonymized before being published. In this study, we investigate trajectory anonymization. Previous methods have limitations in that they cannot be applied for different load network sparseness and cannot preserve the trajectory information. Thus, we propose a DNN-based method that can anonymize trajectories with different load network sparseness and also preserve the trajectory information. Specifically, the trajectories are projected to the latent space using the pre-trained encoder-decoder model, and the latent variables are generalized. Furthermore, to reduce the information loss, we propose a segment-aware trajectory modeling and study the effectiveness of assuming the normal distribution to the latent space. The experimental results using real GPS data show the effectiveness of the proposed method, presenting the improvement in the data reservation rate by approximately 3% and reducing the reconstruction error by approximately 31%. © 2024 The Author(s). <i>IEEJ Transactions on Electrical and Electronic Engineering</i> published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.</p>","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 6","pages":"934-942"},"PeriodicalIF":1.0,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/tee.24254","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144100482","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}

{"title":"Grounding Grids Corrosion Evaluation of Electrified Railway Based on Two-Stage Optimization Algorithm","authors":"Minwu Chen,&nbsp;Yanyang Zhang,&nbsp;Jiadong Han,&nbsp;Yu Cao,&nbsp;Shuai Wang","doi":"10.1002/tee.24219","DOIUrl":"https://doi.org/10.1002/tee.24219","url":null,"abstract":"<p>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.</p>","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}

{"title":"Electrical Stress on Semiconductor Devices Mounted on PCB during Electrostatic Elimination by Corona Discharge Ionizer","authors":"Aguri Nakano,&nbsp;Makoto Okano,&nbsp;Takashi Terashige","doi":"10.1002/tee.24245","DOIUrl":"https://doi.org/10.1002/tee.24245","url":null,"abstract":"<p>Semiconductor devices mounted on printed circuit boards may be damaged by electrical stresses based on induced voltages due to the electric field generated by corona discharge ionizers during the static elimination, because the input line connected to the semiconductor device acts as an antenna terminating the electric field. An electrical stress sensor using an operational amplifier with an input line was mounted on a printed circuit board, in order to investigate the input line length dependence of the electrical stress due to the electric field by the ionizer. The results showed that recent scaled-down semiconductor devices may be damaged when the length of the input line exceeds 50 mm during static elimination with the corona discharge ionizer. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.</p>","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 6","pages":"966-968"},"PeriodicalIF":1.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144100688","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}

{"title":"Finite Control Set Model Predictive Control with Feedback-Based Flux-Weakening Operation for PMSM Drives","authors":"Liguo Yang,&nbsp;Hongmei Li,&nbsp;Haonan Zhao,&nbsp;Jiandong Huang,&nbsp;Chao Zhou","doi":"10.1002/tee.24252","DOIUrl":"https://doi.org/10.1002/tee.24252","url":null,"abstract":"<p>Finite control set model predictive control (FCS-MPC) has gained widespread application in permanent magnet synchronous motor (PMSM) drives, especially for the operations below the base speed. In this paper, a novel voltage feedback-based flux-weakening control scheme is proposed to enable FCS-MPC to extend its operation above the base speed. In this method, an extended state observer (ESO)-based ultra-local model is employed as the prediction model to reduce parameter dependence. To realize flux-weakening operation, PMSM's steady-state voltage drop is estimated using the information from ultra-local model. And the magnitude of steady-state voltage drop is then used as the feedback variable to reconstruct a novel voltage control loop. The output of voltage controller automatically modifies the <i>d</i>-axis current reference when motor operates above the base-speed. With the help of voltage control loop, a smooth and automatic flux-weakening operation can be achieved without requiring the motor parameters. The proposed method is verified experimentally under various speed and load conditions. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.</p>","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 6","pages":"956-965"},"PeriodicalIF":1.0,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144100641","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}

{"title":"Research on Object Detection in Complex Scenarios Based on ASA-YOLOv5","authors":"Shoujun Lin,&nbsp;Lixia Deng,&nbsp;Hongyu Zhang,&nbsp;Lingyun Bi,&nbsp;Jinshun Dong,&nbsp;Dapeng Wan,&nbsp;Haiying Liu,&nbsp;Lida Liu","doi":"10.1002/tee.24249","DOIUrl":"https://doi.org/10.1002/tee.24249","url":null,"abstract":"<p>The applications of target detection in complex scenarios cover a wide range of fields, such as pedestrian and vehicle detection in self-driving cars, face recognition and abnormal behavior detection in security monitoring systems, hazardous materials safety detection in public transportation, and so on. These applications demonstrate the importance and the prospect of wide application of target detection techniques in solving practical problems in complex scenarios. However, in these real scenes, there are often problems such as mutual occlusion and scale change. Therefore, how to accurately identify the target in the real complex scenarios has become a big problem to be solved. In order to solve the above problem, the paper proposes a novel algorithm, Adaptive Self-Attention-YOLOv5 (ASA-YOLOv5), which is built upon the YOLOv5s algorithm and demonstrates effectiveness for target identification in complex scenarios. First, the paper implements a fusion mechanism between the trunk and neck networks, enabling the fusion of features across different levels through upsampling and downsampling. This fusion process mitigates detection errors caused by feature loss. Second, the Shuffle Attention mechanism is introduced before upsampling and downsampling to suppress noise and amplify essential semantic information, further enhancing target identification accuracy. Lastly, the Adaptively Spatial Feature Fusion (ASFF) module and Receptive Field Blocks (RFBs) module are added in the head network, and it can improve feature scale invariance and expand the receptive field. The ability of the model to detect the target in the complex scene is improved effectively. Experimental results indicate a notable improvement in the model's mean Average Precision (mAP) by 2.1% on the COCO dataset and 0.7% on the SIXray dataset. The proposed ASA-YOLOv5 algorithm can enhance the effectiveness for target detection in complex scenarios, and it can be widely used in real-world settings. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.</p>","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 6","pages":"876-885"},"PeriodicalIF":1.0,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144100643","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}