Transfer life prediction of gears by cross-domain health indicator construction and multi-hierarchical long-term memory augmented network
Author:
Publisher
Elsevier BV
Subject
Industrial and Manufacturing Engineering,Safety, Risk, Reliability and Quality
Reference38 articles.
1. Macroscopic–microscopic attention in LSTM networks based on fusion features for gear remaining life prediction;Qin;IEEE Trans Ind Electron,2019
2. Machinery health prognostics: a systematic review from data acquisition to RUL prediction;Lei;Mech Syst Signal Process,2018
3. Data-driven prognostic scheme for bearings based on a novel health indicator and gated recurrent unit network;Ni;IEEE Trans Ind Inform,2022
4. A multi-head attention network with adaptive meta-transfer learning for RUL prediction of rocket engines;Pan;Reliab Eng Syst Saf,2022
5. Gated dual attention unit neural networks for remaining useful life prediction of rolling bearings;Qin;IEEE Trans Ind Inform,2020
Cited by 19 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. Generative artificial intelligence and data augmentation for prognostic and health management: Taxonomy, progress, and prospects;Expert Systems with Applications;2024-12
2. A lognormal-normal mixture model for unsupervised health indicator construction and its application into gear remaining useful life prediction;Mechanical Systems and Signal Processing;2024-11
3. A critical review on system architecture, techniques, trends and challenges in intelligent predictive maintenance;Safety Science;2024-09
4. Patch ModernTCN-Mixer: a dual-task temporal convolutional network framework for hybrid implementation of first prediction time detection and remaining useful life prognosis;Measurement Science and Technology;2024-08-20
5. Remaining useful life prediction of machinery based on performance evaluation and online cross-domain health indicator under unknown working conditions;Journal of Manufacturing Systems;2024-08
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