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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:

Dynamic Simulation Model-Driven Fault Diagnosis Method for Bearing under Missing Fault-Type Samples
Junqing Ma, Xingxing Jiang, Baokun Han, et al.
Applied Sciences (2023) Vol. 13, Iss. 5, pp. 2857-2857
Open Access | Times Cited: 13

Showing 13 citing articles:

A systematic literature review of deep learning for vibration-based fault diagnosis of critical rotating machinery: Limitations and challenges
Omri Matania, Itai Dattner, Jacob Bortman, et al.
Journal of Sound and Vibration (2024) Vol. 590, pp. 118562-118562
Closed Access | Times Cited: 15
A dual-discriminator network based on Sobel gradient operator for digital twin-assisted fault diagnosis
Shuyang Luo, Jiachang Qian, Xufeng Huang, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 145, pp. 110155-110155
Closed Access
Fault Diagnosis of Wind Turbine Under Small Sample Condition Based on WSRGAN-GP
Gengchen Li, Ming Hu, Yuhang Shang, et al.
Lecture notes in electrical engineering (2025), pp. 579-588
Closed Access
Multi-scale attention network (MSAN) for track circuits fault diagnosis
Weijie Tao, Xiaowei Li, Jianlei Liu, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
Proceedings of the Cardiff University Engineering Research Conference 2023

(2024)
Open Access | Times Cited: 2
PT-Informer: A Deep Learning Framework for Nuclear Steam Turbine Fault Diagnosis and Prediction
Jiajing Zhou, An Zhao, Zhile Yang, et al.
Machines (2023) Vol. 11, Iss. 8, pp. 846-846
Open Access | Times Cited: 5
Data-model Interactive Health Condition Assessment for Hydropower Unit
Yujie Liu, Jie Liu, Fengyuan Zhang, et al.
Journal of Physics Conference Series (2024) Vol. 2752, Iss. 1, pp. 012020-012020
Open Access | Times Cited: 1
Simulation data-driven fault diagnosis method for metro traction motor bearings under small samples and missing fault samples
Kailin Bi, Aihua Liao, Dingyu Hu, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 10, pp. 105117-105117
Closed Access | Times Cited: 1
The Research on Mechanical Properties and Compressive Behavior of Graphene Foam with Multi-scale Model
Peng Qi, Hanxing Zhu
(2024), pp. 100-104
Open Access
Using DCGAN and WGAN-GP to Generate Artificial Thermal RGB Images for Induction Motors
Sayyed Mahdi Hejazi, Michael Packianather, Yi Liu
(2024), pp. 113-117
Open Access
A Federated Adversarial Fault Diagnosis Method Driven by Fault Information Discrepancy
Jiechen Sun, Funa Zhou, Jie Chen, et al.
Entropy (2024) Vol. 26, Iss. 9, pp. 718-718
Open Access
Enhancing underwater thruster anomaly detection with support vector glow encoding description
Wenliao Du, Zihan Xiong, Pinfang Zhu, et al.
Ocean Engineering (2024) Vol. 314, pp. 119655-119655
Closed Access
A Novel approach using WGAN-GP and Conditional WGAN-GP for Generating Artificial Thermal Images of Induction Motor Faults
Shahd Hejazi, Michael Packianather, Ying Liu
Procedia Computer Science (2023) Vol. 225, pp. 3681-3691
Open Access | Times Cited: 1
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