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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:

A novel deep convolution multi-adversarial domain adaptation model for rolling bearing fault diagnosis
Lanjun Wan, Yuanyuan Li, Keyu Chen, et al.
Measurement (2022) Vol. 191, pp. 110752-110752
Closed Access | Times Cited: 140

Showing 26-50 of 140 citing articles:

Fault diagnosis of nuclear power plant sliding bearing-rotor systems using deep convolutional generative adversarial networks
Qi Li, Weiwei Zhang, Feiyu Chen, et al.
Nuclear Engineering and Technology (2024) Vol. 56, Iss. 8, pp. 2958-2973
Open Access | Times Cited: 5
A universal fault diagnosis framework for marine machinery based on domain adaptation
Yu Guo, Jundong Zhang, Bin Sun, et al.
Ocean Engineering (2024) Vol. 302, pp. 117729-117729
Closed Access | Times Cited: 5
A novel meta-learning network with adversarial domain-adaptation and attention mechanism for cross-domain for train bearing fault diagnosis
Hao Zhong, Deqiang He, Zexian Wei, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 12, pp. 125109-125109
Closed Access | Times Cited: 5
Few-shot learning for estimating gear wear severity towards digital twinning
Roee Cohen, Lior Bachar, Jacob Bortman
Engineering Failure Analysis (2025), pp. 109330-109330
Open 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
Data-driven machinery fault diagnosis: A comprehensive review
Dhiraj Neupane, Mohamed Reda Bouadjenek, Richard Dazeley, et al.
Neurocomputing (2025), pp. 129588-129588
Open Access
Cross-Attribute adaptation networks: Distilling transferable features from multiple sampling-frequency source domains for fault diagnosis of wind turbine gearboxes
Qikang Li, Baoping Tang, Lei Deng, et al.
Measurement (2022) Vol. 200, pp. 111570-111570
Closed Access | Times Cited: 23
Intelligent fault diagnosis via ring-based decentralized federated transfer learning
Lanjun Wan, Jiaen Ning, Yuanyuan Li, et al.
Knowledge-Based Systems (2023) Vol. 284, pp. 111288-111288
Closed Access | Times Cited: 15
Intelligent Diagnosis of Dual-Channel Parallel Rolling Bearings Based on Feature Fusion
Haike Guo, Xiaoqiang Zhao
IEEE Sensors Journal (2024) Vol. 24, Iss. 7, pp. 10640-10655
Closed Access | Times Cited: 4
Research on Fault Prediction Method of Elevator Door System Based on Transfer Learning
Jun Pan, Changxu Shao, Yuefang Dai, et al.
Sensors (2024) Vol. 24, Iss. 7, pp. 2135-2135
Open Access | Times Cited: 4
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
Bearings remaining useful life prediction across equipment-operating conditions based on multisource-multitarget domain adaptation
Shu’ang Li, Xingquan Shen, Jinjie Zhou, et al.
Measurement (2024) Vol. 236, pp. 115026-115026
Closed Access | Times Cited: 4
A novel meta-transfer learning approach via convolutional multi-head self-attention network for few-shot fault diagnosis
Lanjun Wan, Le Huang, Jiaen Ning, et al.
Knowledge-Based Systems (2024) Vol. 299, pp. 112113-112113
Closed Access | Times Cited: 4
Domain reinforcement feature adaptation methodology with correlation alignment for compound fault diagnosis of rolling bearing
Zisheng Wang, Jianping Xuan, Tielin Shi
Expert Systems with Applications (2024), pp. 125594-125594
Closed Access | Times Cited: 4
SFDA-T: A novel source-free domain adaptation method with strong generalization ability for fault diagnosis
Jie Wang, Haidong Shao, Yiming Xiao, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102903-102903
Closed Access | Times Cited: 4
A dynamic weighted joint distribution domain adaptation network for cross-machine fault diagnosis of rolling bearings
Qi Chang, Congcong Fang, Longqing Fan, et al.
Structural Health Monitoring (2025)
Closed Access
KMDSAN: A novel method for cross-domain and unsupervised bearing fault diagnosis
Shuping Wu, Peiming Shi, Xuefang Xu, et al.
Knowledge-Based Systems (2025), pp. 113170-113170
Closed Access
A novel multiple-prototype and domain adversarial network for few-shot cross-domain fault diagnosis
Peiming Shi, Siyang Dai, Xuefang Xu, et al.
Measurement Science and Technology (2025) Vol. 36, Iss. 3, pp. 036134-036134
Closed Access
Interpretable quadratic convolutional residual neural network for bearing fault diagnosis
Zhiyong Luo, Shuping Pan, Xin Dong, et al.
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2025) Vol. 47, Iss. 4
Closed Access
Adversarial contrastive domain-generative learning for bacteria Raman spectrum joint denoising and cross-domain identification
Haiming Yao, Wei Luo, Xue Wang
Engineering Applications of Artificial Intelligence (2025) Vol. 148, pp. 110426-110426
Closed Access
Prediction Model for Newly-Added Sensors to Ocean Buoys: Leveraging Adversarial Loss and Deep Residual LSTM Architecture
Qiguang Zhu, Zhen Shen, Wenjing Qiao, et al.
Digital Signal Processing (2025), pp. 105126-105126
Closed Access
Rolling Bearing Fault Diagnosis Method Based on SWT and Improved Vision Transformer
Shiyi Ren, X. Lou
Sensors (2025) Vol. 25, Iss. 7, pp. 2090-2090
Open Access
A power information guided-variational mode decomposition (PIVMD) and its application to fault diagnosis of rolling bearing
Xinglong Wang, Jiancong Shi, Jun Zhang
Digital Signal Processing (2022) Vol. 132, pp. 103814-103814
Closed Access | Times Cited: 21
A New Method for Quantitative Estimation of Rolling Bearings Under Variable Working Conditions
Yaoxiang Yu, Xi Gu, Weipeng Ma, et al.
IEEE/ASME Transactions on Mechatronics (2023) Vol. 29, Iss. 1, pp. 41-51
Closed Access | Times Cited: 11
A progressive multi-source domain adaptation method for bearing fault diagnosis
Xiaorong Zheng, Zhiwei He, Jiahao Nie, et al.
Applied Acoustics (2023) Vol. 216, pp. 109797-109797
Closed Access | Times Cited: 11

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