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OpenAlex Citation Counts

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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:

Domain-invariant feature fusion networks for semi-supervised generalization fault diagnosis
He Ren, Jun Wang, Weiguo Huang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107117-107117
Closed Access | Times Cited: 18

Showing 18 citing articles:

Deep transfer learning strategy in intelligent fault diagnosis of rotating machinery
Shengnan Tang, Jingtao Ma, Zhengqi Yan, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108678-108678
Closed Access | Times Cited: 27
DP2Net: A discontinuous physical property-constrained single-source domain generalization network for tool wear state recognition
Xuwei Lai, Kai Zhang, Qing Zheng, et al.
Mechanical Systems and Signal Processing (2024) Vol. 215, pp. 111421-111421
Closed Access | Times Cited: 12
Gradient-based domain-augmented meta-learning single-domain generalization for fault diagnosis under variable operating conditions
Chuanxia Jian, Heen Chen, Chaobin Zhong, et al.
Structural Health Monitoring (2024) Vol. 23, Iss. 6, pp. 3904-3920
Closed Access | Times Cited: 5
Contrast-Assisted Domain-Specificity-Removal Network for Semi-Supervised Generalization Fault Diagnosis
Qiuyu Song, Xingxing Jiang, Jie Liu, et al.
IEEE Transactions on Neural Networks and Learning Systems (2024) Vol. 36, Iss. 3, pp. 5403-5416
Closed Access | Times Cited: 5
Causality-inspired multi-source domain generalization method for intelligent fault diagnosis under unknown operating conditions
Hongbo Ma, Jiacheng Wei, Guowei Zhang, et al.
Reliability Engineering & System Safety (2024) Vol. 252, pp. 110439-110439
Closed Access | Times Cited: 5
Dual disentanglement domain generalization method for rotating Machinery fault diagnosis
Guowei Zhang, Xianguang Kong, Hongbo Ma, et al.
Mechanical Systems and Signal Processing (2025) Vol. 228, pp. 112460-112460
Closed Access
Multiple classifiers inconsistency-based deep adversarial domain generalization method for cross-condition fault diagnosis in rotating systems
Lei Gao, Qinhe Gao, Zhihao Liu, et al.
Reliability Engineering & System Safety (2025), pp. 111017-111017
Closed Access
Deep subdomain adversarial network with self-supervised learning for aero-engine high speed bearing fault diagnosis with unknown working conditions
Huadong Shi, Siyan Cao, Hongfu Zuo, et al.
Measurement (2024) Vol. 241, pp. 115668-115668
Closed Access | Times Cited: 2
A two-stage learning framework for imbalanced semi-supervised domain generalization fault diagnosis under unknown operating conditions
Chuanxia Jian, Heen Chen, Yinhui Ao, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102878-102878
Closed Access | Times Cited: 2
Simulation data-driven attention fusion network with multi-similarity metric: A single-domain generalization diagnostic method for tie rod bolt loosening of a rod-fastening rotor system
Chen Zhou, Jun He, Xin Xiong, et al.
Measurement (2024) Vol. 240, pp. 115565-115565
Closed Access | Times Cited: 1
Multi-Sensor Graph Adaptive Federated Generalization for Helicopter Transmission System Fault Diagnosis
Kuangchi Sun, Aijun Yin
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-11
Closed Access | Times Cited: 1
Shuffle-fusion pyramid network for bearing fault diagnosis under noisy environments
Cheng Zhao, Linfeng Deng, Yuanwen Zhang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 11, pp. 116133-116133
Closed Access | Times Cited: 1
Domain generalization for rotating machinery fault diagnosis: A survey
Yiming Xiao, Haidong Shao, Shen Yan, et al.
Advanced Engineering Informatics (2024) Vol. 64, pp. 103063-103063
Closed Access | Times Cited: 1
Adversarial-Causal Representation Learning Networks for Machine fault diagnosis under unseen conditions based on vibration and acoustic signals
Fei Wu, Zhuohang Xiang, Dengyu Xiao, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 139, pp. 109550-109550
Closed Access
Adaptive reconstruct feature difference network for open set domain generalization fault diagnosis
Mengyu Liu, Zhe Cheng, Yu Yang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 142, pp. 109895-109895
Closed Access
域泛化机械故障诊断研究进程与展望
HaiDong SHAO, YiMing XIAO, Shen YAN, et al.
Scientia Sinica Technologica (2024) Vol. 55, Iss. 1, pp. 14-32
Closed Access
Multi-source data fusion for intelligent diagnosis based on generalized representation
Weimin Peng, Ai−Hong Chen, Jing Chen, et al.
Expert Systems with Applications (2024), pp. 126267-126267
Closed Access
A self-improving fault diagnosis method for intershaft bearings with missing training samples
Jiaxin Feng, Y.J. Bi, Hao Wang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 225, pp. 112260-112260
Closed Access
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