A Semi-Supervised Matrixized Graph Embedding Machine for Roller Bearing Fault Diagnosis Under Few-Labeled Samples
Author:
Affiliation:
1. School of Mechanical Engineering, Anhui University of Technology, Ma'anshan, China
2. College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China
Funder
National Natural Science Foundation of China
Outstanding Youth Fund of Universities in Anhui Province of China
University Natural Science Research Project of Anhui Province
State Key Laboratory of Traction Power
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/9424/10355676/10097541.pdf?arnumber=10097541
Reference35 articles.
1. Artificial intelligence for fault diagnosis of rotating machinery: A review
2. A comprehensive survey on support vector machine classification: Applications, challenges and trends
3. Online Semisupervised Broad Learning System for Industrial Fault Diagnosis
4. Fault detection and diagnosis of a blade pitch system in a floating wind turbine based on Kalman filters and artificial neural networks
5. A new deep auto-encoder method with fusing discriminant information for bearing fault diagnosis
Cited by 8 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. Nonlinear group constrained mode decomposition and its application in gear fault diagnosis;Measurement Science and Technology;2024-09-02
2. Fault diagnosis using variational autoencoder GAN and focal loss CNN under unbalanced data;Structural Health Monitoring;2024-07-24
3. Motor PHM on Edge Computing with Anomaly Detection and Fault Severity Estimation through Compressed Data Using PCA and Autoencoder;Machine Learning and Knowledge Extraction;2024-06-28
4. Adaptive Low-Rank Tensor Estimation Model Based Multichannel Weak Fault Detection for Bearings;Sensors;2024-06-09
5. Optimal margin distribution matrix machine;Expert Systems with Applications;2024-04
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