Machinery fault diagnostic method based on numerical simulation driving partial transfer learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Engineering,General Materials Science
Link
https://link.springer.com/content/pdf/10.1007/s11431-023-2496-6.pdf
Reference48 articles.
1. Jin Y R, Qin C J, Zhang Z N, et al. A multi-scale convolutional neural network for bearing compound fault diagnosis under various noise conditions. Sci China Tech Sci, 2022, 65: 2551–2563
2. Zhou X, Zhou H C, He Y M, et al. Harmonic reducer in-situ fault diagnosis for industrial robots based on deep learning. Sci China Tech, 2022, 65: 2116–2126
3. Liu Y Q, Chen Z G, Wang K Y, et al. Surface wear evolution of traction motor bearings in vibration environment of a locomotive during operation. Sci China Tech Sci, 2022, 65: 920–931
4. Di Z Y, Shao H D, Xiang J W. Ensemble deep transfer learning driven by multisensor signals for the fault diagnosis of bevel-gear cross-operation conditions. Sci China Tech Sci, 2021, 64: 481–492
5. Huang H R, Li K, Su W S, et al. An improved empirical wavelet transform method for rolling bearing fault diagnosis. Sci China Tech Sci, 2020, 63: 2231–2240
Cited by 4 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 novel multi-channel CNN-LSTM and transformer-based network for diesel engine misfire diagnosis under different noise conditions;Science China Technological Sciences;2024-08-21
2. A novel method for vibration signal transmission and attenuation analysis in complex planetary gearboxes;Science China Technological Sciences;2024-08-20
3. A deep targeted transfer network with clustering pseudo-label learning for fault diagnosis across different Machines;Mechanical Systems and Signal Processing;2024-05
4. Towards Zero-Fault Sample Scenarios: A Cyclegan Variant for Enhanced Bearing Fault Data Generation and Diagnosis;2024
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