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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:

Supervised Contrastive Learning-Based Domain Adaptation Network for Intelligent Unsupervised Fault Diagnosis of Rolling Bearing
Yongchao Zhang, Zhaohui Ren, Shihua Zhou, et al.
IEEE/ASME Transactions on Mechatronics (2022) Vol. 27, Iss. 6, pp. 5371-5380
Closed Access | Times Cited: 76

Showing 1-25 of 76 citing articles:

Digital twin-driven intelligent assessment of gear surface degradation
Ke Feng, Jinchen Ji, Yongchao Zhang, et al.
Mechanical Systems and Signal Processing (2022) Vol. 186, pp. 109896-109896
Closed Access | Times Cited: 312
Deep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016
Xiaohan Chen, Rui Yang, Yihao Xue, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-21
Open Access | Times Cited: 185
Physics-Informed Residual Network (PIResNet) for rolling element bearing fault diagnostics
Qing Ni, Jinchen Ji, Benjamin Halkon, et al.
Mechanical Systems and Signal Processing (2023) Vol. 200, pp. 110544-110544
Open Access | Times Cited: 173
Digital twin-driven partial domain adaptation network for intelligent fault diagnosis of rolling bearing
Yongchao Zhang, Jinchen Ji, Zhaohui Ren, et al.
Reliability Engineering & System Safety (2023) Vol. 234, pp. 109186-109186
Open Access | Times Cited: 167
Universal source-free domain adaptation method for cross-domain fault diagnosis of machines
Yongchao Zhang, Zhaohui Ren, Ke Feng, et al.
Mechanical Systems and Signal Processing (2023) Vol. 191, pp. 110159-110159
Closed Access | Times Cited: 90
Integrated intelligent fault diagnosis approach of offshore wind turbine bearing based on information stream fusion and semi-supervised learning
Yongchao Zhang, Kun Yu, Zihao Lei, et al.
Expert Systems with Applications (2023) Vol. 232, pp. 120854-120854
Closed Access | Times Cited: 74
Modified Varying Index Coefficient Autoregression Model for Representation of the Nonstationary Vibration From a Planetary Gearbox
Yuejian Chen, Meng Rao, Ke Feng, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-12
Closed Access | Times Cited: 56
An Adaptive Domain Adaptation Method for Rolling Bearings’ Fault Diagnosis Fusing Deep Convolution and Self-Attention Networks
Xiao Yu, Youjie Wang, Zhongting Liang, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-14
Closed Access | Times Cited: 45
Multi-modal data cross-domain fusion network for gearbox fault diagnosis under variable operating conditions
Yongchao Zhang, Jinliang Ding, Yongbo Li, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108236-108236
Closed Access | Times Cited: 41
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
Dynamic Model-Assisted Bearing Remaining Useful Life Prediction Using the Cross-Domain Transformer Network
Yongchao Zhang, Ke Feng, Jinchen Ji, et al.
IEEE/ASME Transactions on Mechatronics (2022) Vol. 28, Iss. 2, pp. 1070-1080
Closed Access | Times Cited: 49
MMFNet: Multisensor Data and Multiscale Feature Fusion Model for Intelligent Cross-Domain Machinery Fault Diagnosis
Yongchao Zhang, Ke Feng, Hui Ma, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-11
Closed Access | Times Cited: 40
Time-frequency supervised contrastive learning via pseudo-labeling: An unsupervised domain adaptation network for rolling bearing fault diagnosis under time-varying speeds
Bin Pang, Qiuhai Liu, Zhenduo Sun, et al.
Advanced Engineering Informatics (2023) Vol. 59, pp. 102304-102304
Closed Access | Times Cited: 39
IFD-MDCN: Multibranch denoising convolutional networks with improved flow direction strategy for intelligent fault diagnosis of rolling bearings under noisy conditions
Sheng Li, Jinchen Ji, Yadong Xu, et al.
Reliability Engineering & System Safety (2023) Vol. 237, pp. 109387-109387
Open Access | Times Cited: 33
Multi-sensor open-set cross-domain intelligent diagnostics for rotating machinery under variable operating conditions
Yongchao Zhang, Jinchen Ji, Zhaohui Ren, et al.
Mechanical Systems and Signal Processing (2023) Vol. 191, pp. 110172-110172
Closed Access | Times Cited: 24
Domain Adaptation Networks With Parameter-Free Adaptively Rectified Linear Units for Fault Diagnosis Under Variable Operating Conditions
Yongyi Chen, Dan Zhang, Ruqiang Yan
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 11, pp. 16872-16885
Closed Access | Times Cited: 24
A unified out-of-distribution detection framework for trustworthy prognostics and health management in renewable energy systems
Wenzhen Xie, Te Han, Zhongyi Pei, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 125, pp. 106707-106707
Closed Access | Times Cited: 23
Federated transfer learning for machinery fault diagnosis: A comprehensive review of technique and application
Quan Qian, Bin Zhang, Chuan Li, et al.
Mechanical Systems and Signal Processing (2024) Vol. 223, pp. 111837-111837
Closed Access | Times Cited: 10
Generative adversarial networks driven by multi-domain information for improving the quality of generated samples in fault diagnosis
Zhijun Ren, Dawei Gao, Yongsheng Zhu, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 124, pp. 106542-106542
Closed Access | Times Cited: 20
False alarm reduction in drilling process monitoring using virtual sample generation and qualitative trend analysis
Yupeng Li, Weihua Cao, R. Bhushan Gopaluni, et al.
Control Engineering Practice (2023) Vol. 133, pp. 105457-105457
Closed Access | Times Cited: 17
Source-free domain adaptation method for fault diagnosis of rotation machinery under partial information
Aobo Yu, Bolin Cai, Qiujie Wu, et al.
Reliability Engineering & System Safety (2024) Vol. 248, pp. 110181-110181
Closed Access | Times Cited: 7
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
Double-level discriminative domain adaptation network for cross-domain fault diagnosis
Yufeng Li, Xinghan Xu, Lei Hu, et al.
Applied Intelligence (2025) Vol. 55, Iss. 5
Closed Access
A survey on machine learning approaches for uncertainty quantification of engineering systems
Yan Shi, Pengfei Wei, Ke Feng, et al.
Machine learning for computational science and engineering (2025) Vol. 1, Iss. 1
Open Access
Deep feature interactive network for machinery fault diagnosis using multi-source heterogeneous data
Mengqi Miao, Jianbo Yu
Reliability Engineering & System Safety (2023) Vol. 242, pp. 109795-109795
Closed Access | Times Cited: 14
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