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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:

Data augmentation on fault diagnosis of wind turbine gearboxes with an enhanced flow-based generative model
Wenliao Du, Pengxiang Zhu, Ziqiang Pu, et al.
Measurement (2023) Vol. 225, pp. 113985-113985
Closed Access | Times Cited: 9

Showing 9 citing articles:

A new chiller fault diagnosis method under the imbalanced data environment via combining an improved generative adversarial network with an enhanced deep extreme learning machine
Wenxin Yang, Hanyuan Zhang, Jit Bing Lim, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 137, pp. 109218-109218
Closed Access | Times Cited: 17
Wind Turbine Fault Diagnosis for Class-Imbalance and Small-Size Data Based on Stacked Capsule Autoencoder
Xianbo Wang, Hao Chen, Jing Zhao, et al.
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 11, pp. 12694-12704
Closed Access | Times Cited: 7
Research on Cross-Domain Generative Diagnosis for Oil and Gas Pipeline Defect Based on Limited Field Data
Junming Yao, Wei Liang, Zhongmin Xiao
Energy (2025), pp. 135086-135086
Closed Access
Improved deep transfer learning and transmission error based method for gearbox fault diagnosis with limited test samples
Hongbo Yang, Zeyu Wang, Miao Xu, et al.
Mechanical Systems and Signal Processing (2025) Vol. 230, pp. 112593-112593
Closed Access
Privacy-preserving intelligent fault diagnostics for wind turbine clusters using federated stacked capsule autoencoder
Hao Chen, Xianbo Wang, Zhi-Xin Yang, et al.
Expert Systems with Applications (2024) Vol. 254, pp. 124256-124256
Closed Access | Times Cited: 3
Data-augmented trend-fluctuation representations by interpretable contrastive learning for wind power forecasting
Yongning Zhao, Haohan Liao, Yuan Zhao, et al.
Applied Energy (2024) Vol. 380, pp. 125052-125052
Closed Access | Times Cited: 2
Surrounding Rock Squeezing Classification in Underground Engineering Using a Hybrid Paradigm of Generative Artificial Intelligence and Deep Ensemble Learning
Shouye Cheng, Xin Yin, Feng Gao, et al.
Mathematics (2024) Vol. 12, Iss. 23, pp. 3832-3832
Open Access | Times Cited: 1
Enhanced Data Augmentation for Bearing Fault Diagnosis by Using a Spectral Flow Model
Xiaoyun Gong, Mengxuan Hao, Chuan Li, et al.
(2024), pp. 405-409
Closed 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
Fault diagnosis of rotating machinery using a signal processing technique and lightweight model based on mechanical structural characteristics
Maodong Niu, Shangjun Ma, Haifeng Zhu, et al.
Measurement (2024), pp. 116505-116505
Closed Access
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