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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:

Interpretable physics-informed domain adaptation paradigm for cross-machine transfer diagnosis
Chao He, Hongmei Shi, Xiaorong Liu, et al.
Knowledge-Based Systems (2024) Vol. 288, pp. 111499-111499
Closed Access | Times Cited: 20

Showing 20 citing articles:

Interpretable modulated differentiable STFT and physics-informed balanced spectrum metric for freight train wheelset bearing cross-machine transfer fault diagnosis under speed fluctuations
Chao He, Hongmei Shi, Ruixin Li, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102568-102568
Open Access | Times Cited: 17
Transfer Learning for Prognostics and Health Management: Advances, Challenges, and Opportunities
Ruqiang Yan, Weihua Li, Siliang Lu, et al.
Journal of Dynamics Monitoring and Diagnostics (2024)
Open Access | Times Cited: 5
Unsupervised GAN with Fine-Tuning: A Novel Framework for Induction Motor Fault Diagnosis in Scarcely Labeled Sample Scenarios
Xin Chen, Zaigang Chen, Shiqian Chen, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-11
Closed Access | Times Cited: 5
A novel sliding mixing graph contrastive domain adaptation method for fault diagnosis under time-varying speeds
Kai Chen, Zong Meng, Dengyun Sun, et al.
Expert Systems with Applications (2025), pp. 126576-126576
Closed Access
SIGTN: A Novel Structural Infomax Graph Transfer Networks for Rotating Machinery Fault Diagnosis in Cross-Condition and Cross-Equipment Scenarios
Kongliang Zhang, Hongkun Li, Shunxin Cao, et al.
Reliability Engineering & System Safety (2025), pp. 110898-110898
Closed Access
A Novel Framework Based on Complementary Views for Fault Diagnosis with Cross-Attention Mechanisms
Xiaorong Liu, Zhonghan Chen, Dongfeng Hu, et al.
Electronics (2025) Vol. 14, Iss. 5, pp. 886-886
Open Access
Integrating intrinsic information: A novel open set domain adaptation network for cross-domain fault diagnosis with multiple unknown faults
Yuteng Zhang, Hongliang Zhang, Bin Chen, et al.
Knowledge-Based Systems (2024) Vol. 299, pp. 112100-112100
Closed Access | Times Cited: 4
Deep Multilayer Sparse Regularization Time-Varying Transfer Learning Networks With Dynamic Kullback–Leibler Divergence Weights for Mechanical Fault Diagnosis
Feiyu Lu, Qingbin Tong, Xuedong Jiang, et al.
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 11, pp. 13452-13462
Closed Access | Times Cited: 4
Attention guided partial domain adaptation for interpretable transfer diagnosis of rotating machinery
Gang Wang, Dongdong Liu, Jiawei Xiang, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102708-102708
Closed Access | Times Cited: 3
An improved envelope spectrum via Hoyer index-gram for bearing fault extraction
Tian Tian, Guiji Tang, Xiaolong Wang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 7, pp. 076124-076124
Open Access | Times Cited: 2
Drill Tools Sticking Prediction Based on Adaptive Long Short-Term Memory
Honglin Wu, Zhongbin Wang, Lei Si, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 8, pp. 086134-086134
Closed Access | Times Cited: 2
Enhancing Fault Diagnosis in Mechanical Systems with Graph Neural Networks Addressing Class Imbalance
Wenhao Lu, Wei Wang, Xuefei Qin, et al.
Mathematics (2024) Vol. 12, Iss. 13, pp. 2064-2064
Open Access | Times Cited: 2
Adaptive feature consolidation residual network for exemplar-free continuous diagnosis of rotating machinery with fault-type increments
Yan Zhang, Changqing Shen, Xingli Zhong, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102715-102715
Closed Access | Times Cited: 2
Granularity knowledge-sharing supervised contrastive learning framework for long-tailed fault diagnosis of rotating machinery
Shuyuan Chang, Liyong Wang, Mingkuan Shi, et al.
Knowledge-Based Systems (2024) Vol. 301, pp. 112354-112354
Closed Access | Times Cited: 2
Multiscale ECA network: a rotation mechanical domain adaptation method with minimal class confusion
Xueyi Li, Tianyu Yu, Kaiyu Su, et al.
Structural Health Monitoring (2024)
Closed Access | Times Cited: 1
AMCW-DFFNSA: An interpretable deep feature fusion network for noise-robust machinery fault diagnosis
Yan Han, Sipeng Lv, Qingqing Huang, et al.
Knowledge-Based Systems (2024) Vol. 301, pp. 112361-112361
Closed Access | Times Cited: 1
Empirical variational mode extraction and its application in bearing fault diagnosis
Bin Pang, Yanjie Zhao, Changqi Yu, et al.
Applied Acoustics (2024) Vol. 228, pp. 110349-110349
Closed Access | Times Cited: 1
MSTD: a framework for rolling bearing fault diagnosis based on multi-scale and soft-threshold denoising
Zhiwei Qiao, Dechen Yao, Jianwei Yang, et al.
Nondestructive Testing And Evaluation (2024), pp. 1-21
Closed Access | Times Cited: 1
Lightweight Ghost Enhanced Feature Attention Network: An Efficient Intelligent Fault Diagnosis Method under Various Working Conditions
Huaihao Dong, Kai Zheng, Siguo Wen, et al.
Sensors (2024) Vol. 24, Iss. 11, pp. 3691-3691
Open Access
DPICEN: Deep Physical Information Consistency Embedded Network for Bearing Fault Diagnosis under Unknown Domain
Feiyu Lu, Qingbin Tong, Xuedong Jiang, et al.
Reliability Engineering & System Safety (2024) Vol. 252, pp. 110454-110454
Closed Access
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