2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)最新文献_第2页

Design of Linear Motor for Medium and Low Speed Maglev Train 中低速磁悬浮列车直线电机的设计

2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2024-01-26 DOI: 10.1109/ICPECA60615.2024.10471098

Ao Liu, Xin Zhang, Liwei Zhang, Neimeng Yang, Jiachen Song, Yuhang Wang

引用次数: 0

Application of Power Internet of Things Technology in Fault Diagnosis Platform for Synchronous Condenser 电力物联网技术在同步冷凝器故障诊断平台中的应用

2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2024-01-26 DOI: 10.1109/ICPECA60615.2024.10471092

Liu Ya'nan, Xu Gang, Xia Chao, Jianyong Hu, Jianchao Wu

{"title":"Application of Power Internet of Things Technology in Fault Diagnosis Platform for Synchronous Condenser","authors":"Liu Ya'nan, Xu Gang, Xia Chao, Jianyong Hu, Jianchao Wu","doi":"10.1109/ICPECA60615.2024.10471092","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10471092","url":null,"abstract":"The Synchronous condenser remote diagnosis platform is built under the background of the power Internet of Things technology, with the power grid as the hub, and through data warehouse and data replication technologies to build a data center, achieving the sharing and exchange of information data throughout the company. We apply advanced big data technology to mine operating data and build a reliable, secure, and linearly scalable big data system. With the help of data transformation, outliers can be handled, standardization, generalization, and data aggregation, the inference of fault diagnosis knowledge base will been carried out. Utilizing data warehouse and data mining technology to analyze various indicators in the operation, maintenance and management of the synchronous condenser, we could establish a safety warning evaluation system based on massive data, and combine system operation status estimation technology to ensure the health of the synchronous condenser, achieving precise prediction and coordinated control. Finally, a comparative analysis was conducted between the new system and the traditional status monitoring system, and the superiority of the new system is given.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"10 9","pages":"28-32"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

XGBSO: An Employability Assessment Model XGBSO：就业能力评估模型

2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2024-01-26 DOI: 10.1109/ICPECA60615.2024.10470961

Xue Tu

{"title":"XGBSO: An Employability Assessment Model","authors":"Xue Tu","doi":"10.1109/ICPECA60615.2024.10470961","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10470961","url":null,"abstract":"To meet the increasing competition in the marketplace during the post epidemic era, it is crucial for the IT industry to swiftly assess and select job seekers while identifying the enhancement skills required for individual job seekers. Current research lacks model optimization and predominantly uses a combination of machine learning methods. However, this study addresses this gap by employing multiple machine learning algorithms based on annual developer survey data from Stack Overflow to predict job seeker skill judgments and quantitative feature scores. The optimized XGBoost model based on the snake optimization algorithm (XGBSO) shows superior performance in accuracy and F1 score compared to other models, accurately predicting the job search ability of programmers. Feature weighting analysis reveals that computer skill is the most crucial feature. The XGBSO model is validated through ROC curves and AUC-ROC values, displaying an accuracy of 0.838 and an F1 score of 0.855, thus indicating excellent performance. The proposed XGBSO model serves as an effective tool for assessing programmers' job search ability and yields significant results.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"85 11","pages":"392-397"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Double Fuzzy PID Control in PMLSM Variable Theory Research PMLSM 变量理论研究中的双模糊 PID 控制

2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2024-01-26 DOI: 10.1109/ICPECA60615.2024.10470990

Junqiang Peng, Zhihao Cai

引用次数: 0

Capacity Calculation of Static Frequency Converter for 300Mvar Synchronous Condenser 用于 300Mvar 同步冷凝器的静态变频器容量计算

2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2024-01-26 DOI: 10.1109/ICPECA60615.2024.10471183

Yin Zhang, Yazhou Yuan, Ruiqi Zhang, Qiang Wu, Lingfeng Sun, Wenqian Ji, Hongchao Zhu, Shaoxing Zhao

引用次数: 0

Study on Current Controller of Doubly-Fed Induction Generator with Variable Parameters 参数可变的双馈感应发电机电流控制器研究

2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2024-01-26 DOI: 10.1109/ICPECA60615.2024.10471129

Maimaitireyimu Abulizi, Wenjie Shi, Yangteng Hu, Maidina Bahati, Chao Zhang

引用次数: 0

Research on the Robustness of Behavior Recognition Model in Power Safety Monitoring Based on Neural Network Algorithm 基于神经网络算法的电力安全监测行为识别模型鲁棒性研究

2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2024-01-26 DOI: 10.1109/ICPECA60615.2024.10471155

Ningping Tang, Bo Gao

{"title":"Research on the Robustness of Behavior Recognition Model in Power Safety Monitoring Based on Neural Network Algorithm","authors":"Ningping Tang, Bo Gao","doi":"10.1109/ICPECA60615.2024.10471155","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10471155","url":null,"abstract":"With the continuous development of power systems and the deepening of power safety supervision work, it is particularly important to effectively identify and monitor the behavior of power safety supervision personnel. This research aims to improve the accuracy and real-time performance of personnel behavior recognition in the field of electric power safety supervision through advanced neural network technology. First, this study conducts an in-depth analysis of the common behaviors of electric power safety supervisors, including daily inspections, accident handling, equipment maintenance and other tasks. On this basis, a behavior recognition model based on neural network algorithm is proposed. This model combines deep learning and pattern recognition methods and can accurately classify various behaviors of power safety supervisors. Secondly, a large amount of field data was used for training and testing in the study to ensure the robustness and generalization ability of the model. Furthermore, this study focuses on the real-time and adaptability of the algorithm. Taking into account the particularity of power safety supervision, by adjusting the structure and parameters of the neural network, the algorithm can perform behavior recognition more efficiently in real-time scenarios, and the training of neural networks optimizes the performance of the algorithm. Experiments have proven that the proposed behavior recognition model based on neural network algorithm has high accuracy and robustness in classifying human behavior.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"86 2","pages":"995-999"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and Research of a DC Charging Station Measurement and Monitoring System for Electric Vehicles Based on DC Measurement Chips 基于直流测量芯片的电动汽车直流充电站测量和监控系统的设计与研究

2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2024-01-26 DOI: 10.1109/ICPECA60615.2024.10471104

Suqin Xiong, Yang Li, Qiuyang Li, Jianning Guo

引用次数: 0

Design and application of a portable electric power distribution gateway operation and maintenance test tool based on cloud edge collaboration 基于云边缘协作的便携式配电网关运维测试工具的设计与应用

2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2024-01-26 DOI: 10.1109/ICPECA60615.2024.10471025

Ruijiang Zeng, Shu Huang

{"title":"Design and application of a portable electric power distribution gateway operation and maintenance test tool based on cloud edge collaboration","authors":"Ruijiang Zeng, Shu Huang","doi":"10.1109/ICPECA60615.2024.10471025","DOIUrl":"https://doi.org/10.1109/ICPECA60615.2024.10471025","url":null,"abstract":"As the key equipment of the intelligent electric power distribution room, the electric power distribution gateway is the main equipment to realize the distribution IoT. In order to ensure its normal operation, regular operation and maintenance are required. At present, the research on the operation and maintenance technology of the intelligent electric power distribution room mostly focuses on the detection of the communication protocol of the intelligent terminal and the design of the operation and maintenance master station platform, while the research on the on-site operation and maintenance tools of the electric power distribution gateway is difficult to find. Therefore, this paper studies this technology. First, based on the architecture of “cloud management edge and end” of the electric power distribution IoT, the automatic closed-loop test architecture of cloud edge collaboration is designed, and the cloud edge collaboration function of the portable operation and maintenance test tool is defined. Secondly, the software and hardware design as well as the portable design of the on-site portable operation and maintenance testing tools were elaborated, ensuring the lightweight and portable operation and maintenance tool while ensuring the cloud edge collaborative operation and maintenance testing function. Finally, the feasibility of the technology is verified by field application, and the intelligent operation and maintenance level of the electric power distribution gateway is greatly improved.","PeriodicalId":518671,"journal":{"name":"2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA)","volume":"87 5","pages":"267-274"},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","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 Attitude Resolution Method Based on Improved Complementary Filtering 基于改进互补滤波的姿态分辨率方法研究

2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA) Pub Date : 2024-01-26 DOI: 10.1109/ICPECA60615.2024.10470999

Hongbin Yu, Shuangyang Yang

引用次数: 0