Deep multi-scale convolutional transfer learning network: A novel method for intelligent fault diagnosis of rolling bearings under variable working conditions and domains-Reference-Cited by-同舟云学术

Deep multi-scale convolutional transfer learning network: A novel method for intelligent fault diagnosis of rolling bearings under variable working conditions and domains

Published:2020-09 Issue: Volume:407 Page:24-38
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Zhao Bo,Zhang Xianmin^ORCID,Zhan Zhenhui,Pang Shuiquan

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference48 articles.

1. Cross-domain fault diagnosis using knowledge transfer strategy: a review;Zheng;IEEE Access,2019

2. Machinery health prognostics: a systematic review from data acquisition to RUL prediction;Lei;Mech. Syst. Signal Process.,2018

3. Data-driven fault diagnosis method based on compressed sensing and improved multi-scale network;Hu;IEEE Trans. Ind. Electron.,2019

4. Fault diagnosis of planetary gearbox using a novel semi-supervised method of multiple association layers networks;Zhang;Mech. Syst. Signal Process.,2019

5. Deep decoupling convolutional neural network for intelligent compound fault diagnosis;Huang;IEEE Access,2018

Cited by 122 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 source free robust domain adaptation approach with pseudo-labels uncertainty estimation for rolling bearing fault diagnosis under limited sample conditions;Knowledge-Based Systems;2024-11

2. Parallel quantized dual-level fully connected classifier for bearing fault diagnosis;Engineering Applications of Artificial Intelligence;2024-10

3. Effects of various information scenarios on layer-wise relevance propagation-based interpretable convolutional neural networks for air handling unit fault diagnosis;Building Simulation;2024-08-19

4. A hybrid dynamic adversarial domain adaptation network with multi-channel attention mechanism for rotating machinery unsupervised fault diagnosis under varying operating conditions;Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science;2024-07-26

5. A hybrid network TEdgeNeXt for data-limited and resource-constrained fault diagnosis;Journal of Vibration and Control;2024-07-23