J Tian, C Chen, W Shen, F Sun, R Xiong - Energy Storage Materials, 2023 - Elsevier
Accurate state of charge (SOC) constitutes the basis for reliable operations of lithium-ion batteries. The deep learning technique, a game changer in many fields, has recently …
X Chen, H Shao, Y Xiao, S Yan, B Cai, B Liu - Mechanical Systems and …, 2023 - Elsevier
Most of the existing research on unsupervised cross-domain intelligent fault diagnosis is based on single-source domain adaptation, which fails to simultaneously utilize various …
Y Xiao, H Shao, SY Han, Z Huo… - IEEE/ASME Transactions …, 2022 - ieeexplore.ieee.org
Unsupervised cross-domain fault diagnosis of bearings has practical significance; however, the existing studies still face some problems. For example, transfer diagnosis scenarios are …
H Tao, J Qiu, Y Chen, V Stojanovic, L Cheng - Journal of the Franklin …, 2023 - Elsevier
In recent years, data-driven methods have been widely used in rolling bearing fault diagnosis with great success, which mainly relies on the same data distribution and massive …
Fault diagnosis is efficient to improve the safety, reliability, and cost-effectiveness of industrial machinery. Deep learning has been extensively investigated in fault diagnosis …
Rotating machinery intelligent diagnosis based on deep learning (DL) has gone through tremendous progress, which can help reduce costly breakdowns. However, different …
H Chen, H Luo, B Huang, B Jiang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Over the last decade, transfer learning has attracted a great deal of attention as a new learning paradigm, based on which fault diagnosis (FD) approaches have been intensively …
T Li, Z Zhao, C Sun, R Yan… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Unsupervised domain adaptation (UDA)-based methods have made great progress in mechanical fault diagnosis under variable working conditions. In UDA, three types of …
W Zhang, L Deng, L Zhang, D Wu - IEEE/CAA Journal of …, 2022 - ieeexplore.ieee.org
Transfer learning (TL) utilizes data or knowledge from one or more source domains to facilitate learning in a target domain. It is particularly useful when the target domain has very …