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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:

Transfer learning method for rolling bearing fault diagnosis under different working conditions based on CycleGAN
Jiantong Zhao, Wentao Huang
Measurement Science and Technology (2021) Vol. 33, Iss. 2, pp. 025003-025003
Closed Access | Times Cited: 20

Showing 20 citing articles:

A bearing fault diagnosis method without fault data in new working condition combined dynamic model with deep learning
Kun Xu, Xianguang Kong, Qibin Wang, et al.
Advanced Engineering Informatics (2022) Vol. 54, pp. 101795-101795
Closed Access | Times Cited: 69
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: 30
A domain adaptation method for bearing fault diagnosis using multiple incomplete source data
Qibin Wang, Yuanbing Xu, Shengkang Yang, et al.
Journal of Intelligent Manufacturing (2023) Vol. 35, Iss. 2, pp. 777-791
Closed Access | Times Cited: 27
Convolutional-neural-network-based multi-signals fault diagnosis of induction motor using single and multi-channels datasets
Manar Abdelmaksoud, Marwan Torki, Mohamed El-Habrouk, et al.
Alexandria Engineering Journal (2023) Vol. 73, pp. 231-248
Open Access | Times Cited: 19
Fault diagnosis of rotating parts integrating transfer learning and ConvNeXt model
Zhikai Xing, Yongbao Liu, Qiang Wang, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Biologically inspired compound defect detection using a spiking neural network with continuous time–frequency gradients
Zisheng Wang, Shaochen Li, Jianping Xuan, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103132-103132
Closed Access
Deep Learning in Industrial Machinery: A Critical Review of Bearing Fault Classification Methods
Attiq Ur Rehman, Weidong Jiao, Yonghua Jiang, et al.
Applied Soft Computing (2025), pp. 112785-112785
Closed Access
Alternative multi-label imitation learning framework monitoring tool wear and bearing fault under different working conditions
Zisheng Wang, Jianping Xuan, Tielin Shi
Advanced Engineering Informatics (2022) Vol. 54, pp. 101749-101749
Closed Access | Times Cited: 19
Optimizing the preventive maintenance frequency with causal machine learning
Toon Vanderschueren, Robert Boute, Tim Verdonck, et al.
International Journal of Production Economics (2023) Vol. 258, pp. 108798-108798
Open Access | Times Cited: 11
Adversarial Deep Transfer Learning in Fault Diagnosis: Progress, Challenges, and Future Prospects
Yu Guo, Jundong Zhang, Bin Sun, et al.
Sensors (2023) Vol. 23, Iss. 16, pp. 7263-7263
Open Access | Times Cited: 9
Novel imbalanced subdomain adaption multiscale convolutional network for cross-domain unsupervised fault diagnosis of rolling bearings
Tianlong Huo, Linfeng Deng, Bo Zhang, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 015905-015905
Closed Access | Times Cited: 9
Multisource cross-domain fault diagnosis of rolling bearing based on subdomain adaptation network
Zhichao Wang, Wentao Huang, Yi Chen, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 10, pp. 105109-105109
Closed Access | Times Cited: 8
Prototype-guided bi-level adversarial domain adaptation network for intelligent fault diagnosis of rotating machinery under various working conditions
Jiachen Kuang, Guanghua Xu, Sicong Zhang, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 11, pp. 115014-115014
Closed Access | Times Cited: 8
An Instance and Feature-Based Hybrid Transfer Model for Fault Diagnosis of Rotating Machinery With Different Speeds
Baoxuan Zhao, Changming Cheng, Guanzhen Zhang, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-12
Closed Access | Times Cited: 8
Review of imbalanced fault diagnosis technology based on generative adversarial networks
Hualin Chen, Jianan Wei, Haisong Huang, et al.
Journal of Computational Design and Engineering (2024) Vol. 11, Iss. 5, pp. 99-124
Open Access | Times Cited: 1
Synthetic data generation of vibration signals at different speed and load conditions of transmissions utilizing generative adversarial networks
Timo König, Fabian Wagner, Robin Bäßler, et al.
tm - Technisches Messen (2023) Vol. 90, Iss. 10, pp. 639-649
Closed Access | Times Cited: 2
Cross-domain intelligent fault diagnosis of rolling bearing based on distance metric transfer learning
Hongdi Zhou, Tao Huang, Xixing Li, et al.
Advances in Mechanical Engineering (2022) Vol. 14, Iss. 11, pp. 168781322211357-168781322211357
Open Access | Times Cited: 3
Entropy-Weighted Manifold-Adjusted Transfer Learning for Cross-Condition Fault Diagnosis with Imbalanced and Missing Labels
Z. Zhou, Wen‐Hua Chen
Signal Processing (2024) Vol. 229, pp. 109806-109806
Closed Access
A Review of Rotation Mechanical Fault Diagnosis Research Based on Deep Domain Adaptation
Shun Zhang, Gang Xie, Juan Tian, et al.
(2023), pp. 247-248
Closed Access | Times Cited: 1
A Cross-Domain Bearing Fault Diagnosis Method with Multi-Source Incomplete Data
Qibin Wang, Yuanbing Xu, Shengkang Yang, et al.
SSRN Electronic Journal (2022)
Closed Access | Times Cited: 1
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