An adversarial transfer learning method based on domain distribution prediction for aero-engine fault diagnosis
Author:
Publisher
Elsevier BV
Reference44 articles.
1. Adapting to continuously shifting domains;Bobu,2018
2. An approach for optimal measurements selection on gas turbine engine fault diagnosis;Chen;J. Eng. Gas Turbines Power,2015
3. Gas-path component fault diagnosis for gas turbine engine: a review;Chen,2019
4. A sequential model-based approach for gas turbine performance diagnostics;Chen;Energy,2021
5. State estimation of a physical system with unknown governing equations;Course;Nature,2023
Cited by 3 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. Adaptive neighborhood-perceived contrastive network for early stage fault diagnosis of rolling bearing with limited labeled data;Engineering Applications of Artificial Intelligence;2024-11
2. Ultra-low cycle fatigue life prediction of stainless steel based on transfer learning guided artificial neural network;Engineering Applications of Artificial Intelligence;2024-10
3. Fast Fault Line Selection Technology of Distribution Network Based on MCECA-CloFormer;Applied Sciences;2024-09-13
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