OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
Category-aware dual adversarial domain adaptation model for rolling bearings fault diagnosis under variable conditions
Xingchi Lu, Weiyang Xu, Quan Jiang, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 9, pp. 095104-095104
Closed Access | Times Cited: 7
Xingchi Lu, Weiyang Xu, Quan Jiang, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 9, pp. 095104-095104
Closed Access | Times Cited: 7
Showing 7 citing articles:
SSPENet: Semi-supervised prototype enhancement network for rolling bearing fault diagnosis under limited labeled samples
Xuejian Yao, Xingchi Lu, Quan Jiang, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102560-102560
Closed Access | Times Cited: 11
Xuejian Yao, Xingchi Lu, Quan Jiang, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102560-102560
Closed Access | Times Cited: 11
Review of research on signal decomposition and fault diagnosis of rolling bearing based on vibration signal
Junning Li, Luo Wen-guang, Mengsha Bai
Measurement Science and Technology (2024) Vol. 35, Iss. 9, pp. 092001-092001
Closed Access | Times Cited: 9
Junning Li, Luo Wen-guang, Mengsha Bai
Measurement Science and Technology (2024) Vol. 35, Iss. 9, pp. 092001-092001
Closed Access | Times Cited: 9
RUL prediction method for rolling bearing using convolutional denoising autoencoder and bidirectional LSTM
Xuejian Yao, Junjun Zhu, Quan Jiang, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 3, pp. 035111-035111
Closed Access | Times Cited: 17
Xuejian Yao, Junjun Zhu, Quan Jiang, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 3, pp. 035111-035111
Closed Access | Times Cited: 17
Remaining useful life prediction model of cross-domain rolling bearing via dynamic hybrid domain adaptation and attention contrastive learning
Xingchi Lu, Xuejian Yao, Quan Jiang, et al.
Computers in Industry (2024) Vol. 164, pp. 104172-104172
Closed Access | Times Cited: 5
Xingchi Lu, Xuejian Yao, Quan Jiang, et al.
Computers in Industry (2024) Vol. 164, pp. 104172-104172
Closed Access | Times Cited: 5
Bearing fault diagnosis based on high-confidence pseudo-labels and dual-view multi-adversarial sparse joint attention network under variable working conditions
Cailu Pan, Zhiwu Shang, Wanxiang Li, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108625-108625
Closed Access | Times Cited: 4
Cailu Pan, Zhiwu Shang, Wanxiang Li, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108625-108625
Closed Access | Times Cited: 4
Rolling bearing incipient fault feature extraction using impulse-enhanced sparse time-frequency representation
Hongxuan Zhu, Hongkai Jiang, Renhe Yao, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 10, pp. 105124-105124
Closed Access | Times Cited: 2
Hongxuan Zhu, Hongkai Jiang, Renhe Yao, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 10, pp. 105124-105124
Closed Access | Times Cited: 2
Semi-Supervised Contrastive Transfer Learning Network for Fault Diagnosis of Cross-Working Condition Rolling Bearings
Xingchi Lu, Quan Jiang, Zhengchang Su, et al.
(2024), pp. 1-6
Closed Access
Xingchi Lu, Quan Jiang, Zhengchang Su, et al.
(2024), pp. 1-6
Closed Access
