An Approach Based on Transfer Learning to Lifetime Degradation Rate Prediction of the Dry-Type Transformer
Author:
Affiliation:
1. School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
2. Technology Department, Xi'an Shengxin Science and Technology Development Co., Ltd., Xidian University, Xian, China
Funder
Fundamental Research Funds for the Central Universities
Sichuan Science and Technology Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/41/9913345/09732258.pdf?arnumber=9732258
Reference33 articles.
1. Deep Learning of Transferable Representation for Scalable Domain Adaptation
2. Structure-Preserved Unsupervised Domain Adaptation
3. A Unified Framework for Metric Transfer Learning
4. Wind Turbine Gearbox Failure Identification With Deep Neural Networks
5. Assessment of Power Transformer Paper Ageing Using Wavelet Texture Analysis of Microscopy Images
Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Research on the filling of missing monitoring data under DC bias condition of power transformer;Electric Power Systems Research;2024-06
2. A novel short-term load forecasting approach for data-poor areas based on K-MIFS-XGBoost and transfer-learning;Electric Power Systems Research;2024-04
3. Hybrid Approach to Train Delay Prediction: An Integration of Analytical Model and Deep Learning Techniques;IEEE Transactions on Industrial Electronics;2024
4. Self-Adjusting Domain Adversarial Transfer Learning Algorithm for Power Transformer Lifetime Prediction;IEEE Transactions on Industrial Electronics;2024
5. A Lifetime Prediction Approach Based on Adversarial Variational Auto-Encoder Networks for Dry-Type Power Transformers;2023 IEEE International Conference on Energy Technologies for Future Grids (ETFG);2023-12-03
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3