Semi-supervised clustering-based method for fault diagnosis and prognosis: A case study-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Semi-supervised clustering-based method for fault diagnosis and prognosis: A case study

Published:2022-06 Issue: Volume:222 Page:108405
ISSN:0951-8320
Container-title:Reliability Engineering & System Safety
language:en
Short-container-title:Reliability Engineering & System Safety

Author:

Azar Kamyar,Hajiakhondi-Meybodi Zohreh,Naderkhani Farnoosh

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Safety, Risk, Reliability and Quality

Reference51 articles.

1. Deep learning and its applications to machine health monitoring;Zhao;Mech Syst Signal Process,2019

2. Manufacturing quality prediction using intelligent learning approaches: A comparative study;Bai;Sustainability,2018

3. Condition-based maintenance optimization using neural network-based health condition prediction;Wu;Qual Reliab Eng Int,2013

4. Condition based maintenance optimization for wind power generation systems under continuous monitoring;Tian;Renew Energy,2011

5. A review on machinery diagnostics and prognostics implementing condition-based maintenance;Jardine;Mech Syst Signal Process,2006

Cited by 31 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. A holistic semi-supervised method for imbalanced fault diagnosis of rotational machinery with out-of-distribution samples;Reliability Engineering & System Safety;2024-10

2. A hybrid deep learning model towards fault diagnosis of drilling pump;Applied Energy;2024-10

3. A Monte Carlo Method to Decision-Making in Maintenance Strategies;Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems;2024-09-04

4. STP-Model: A semi-supervised framework with self-supervised learning capabilities for downhole fault diagnosis in sucker rod pumping systems;Engineering Applications of Artificial Intelligence;2024-09

5. Fractional derivative kernel recursive generalized maximum correntropy for RUL prediction of rolling bearings;Mechanical Systems and Signal Processing;2024-08

同舟云学术

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