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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:

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

Showing 1-25 of 74 citing articles:

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
Insights into modern machine learning approaches for bearing fault classification: A systematic literature review
Afzal Ahmed Soomro, Masdi Muhammad, Ainul Akmar Mokhtar, et al.
Results in Engineering (2024) Vol. 23, pp. 102700-102700
Open Access | Times Cited: 18
Graph neural network-based bearing fault diagnosis using Granger causality test
Zhewen Zhang, Lifeng Wu
Expert Systems with Applications (2023) Vol. 242, pp. 122827-122827
Closed Access | Times Cited: 26
Fault diagnosis of wind turbine gearbox under limited labeled data through temporal predictive and similarity contrast learning embedded with self-attention mechanism
Yunyi Zhu, Bin Xie, Anqi Wang, et al.
Expert Systems with Applications (2023) Vol. 245, pp. 123080-123080
Closed Access | Times Cited: 22
A digital twin-driven approach for partial domain fault diagnosis of rotating machinery
Jingyan Xia, Zhuyun Chen, Jiaxian Chen, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 131, pp. 107848-107848
Closed Access | Times Cited: 11
Data-Driven Process Monitoring and Fault Diagnosis: A Comprehensive Survey
Afrânio Melo, Maurício Melo Câmara, José Carlos Pinto
Processes (2024) Vol. 12, Iss. 2, pp. 251-251
Open Access | Times Cited: 11
Transparent Operator Network: A Fully Interpretable Network Incorporating Learnable Wavelet Operator for Intelligent Fault Diagnosis
Qi Li, Hua Li, Wenyang Hu, et al.
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 6, pp. 8628-8638
Closed Access | Times Cited: 11
Spatio-Temporal Feature Alignment Transfer Learning for Cross-Turbine Blade Icing Detection of Wind Turbines
Ruxu Yue, Guoqian Jiang, Xiaohang Jin, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-17
Closed Access | Times Cited: 9
Data-Driven Models Applied to Predictive and Prescriptive Maintenance of Wind Turbine: A Systematic Review of Approaches Based on Failure Detection, Diagnosis, and Prognosis
Rogério Adriano da Fonseca Santiago, Natasha Benjamim Barbosa, Henrique Gomes Mergulhão, et al.
Energies (2024) Vol. 17, Iss. 5, pp. 1010-1010
Open Access | Times Cited: 8
A multiple conditions dual inputs attention network remaining useful life prediction method
Chengying Zhao, Huaitao Shi, Xianzhen Huang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108160-108160
Closed Access | Times Cited: 8
Performance degradation assessment of rolling bearing cage failure based on enhanced CycleGAN
Caizi Fan, Pengfei Wang, Hui Ma, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124697-124697
Closed Access | Times Cited: 8
Knowledge Distillation-Guided Cost-Sensitive Ensemble Learning Framework for Imbalanced Fault Diagnosis
Shuaiqing Deng, Zihao Lei, Guangrui Wen, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 13, pp. 23110-23122
Closed Access | Times Cited: 7
Digital twin-driven discriminative graph learning networks for cross-domain bearing fault recognition
Yadong Xu, Qiubo Jiang, Sheng Li, et al.
Computers & Industrial Engineering (2024) Vol. 193, pp. 110292-110292
Closed Access | Times Cited: 7
Digital Twin-Assisted Fault Diagnosis of Rotating Machinery Without Measured Fault Data
Jingyan Xia, Ruyi Huang, Jipu Li, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-10
Closed Access | Times Cited: 7
A novel metric-based model with the ability of zero-shot learning for intelligent fault diagnosis
Caizi Fan, Yongchao Zhang, Hui Ma, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 129, pp. 107605-107605
Closed Access | Times Cited: 16
A conditional generative model for end-to-end stress field prediction of composite bolted joints
Yong Zhao, Yuming Liu, Qingyuan Lin, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108692-108692
Closed Access | Times Cited: 7
Fault diagnosis of a wave energy converter gearbox based on an Adam optimized CNN-LSTM algorithm
Jichuan Kang, Xu Zhu, Shen Li, et al.
Renewable Energy (2024) Vol. 231, pp. 121022-121022
Open Access | Times Cited: 7
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
A Federated Learning Framework for Cloud–Edge Collaborative Fault Diagnosis of Wind Turbines
Guoqian Jiang, Kai Zhao, Xiufeng Liu, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 13, pp. 23170-23185
Closed Access | Times Cited: 6
A Semi-supervised Gaussian Mixture Variational Autoencoder method for few-shot fine-grained fault diagnosis
Zhiqian Zhao, Yeyin Xu, Jiabin Zhang, et al.
Neural Networks (2024) Vol. 178, pp. 106482-106482
Closed Access | Times Cited: 6
An auto-regulated universal domain adaptation network for uncertain diagnostic scenarios of rotating machinery
Jipu Li, Xiaoge Zhang, Ke Yue, et al.
Expert Systems with Applications (2024) Vol. 249, pp. 123836-123836
Closed Access | Times Cited: 5
Revolution and peak discrepancy-based domain alignment method for bearing fault diagnosis under very low-speed conditions
Seung-Yun Lee, Sungjong Kim, Su J. Kim, et al.
Expert Systems with Applications (2024) Vol. 251, pp. 124084-124084
Closed Access | Times Cited: 5
Cross-Domain Compound Fault Diagnosis of Machine-Level Motors via Time–Frequency Self-Contrastive Learning
Yiming He, Chao Zhao, Weiming Shen
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 7, pp. 9692-9701
Closed Access | Times Cited: 5
A feature cross-fusion HGCN based on feature distillation denoising for fault diagnosis of helicopter tail drive system
Zhaohui Qiao, Aijun Yin, Quan He, et al.
Expert Systems with Applications (2025), pp. 126587-126587
Closed Access
Transparent information fusion network: An explainable network for multi-source bearing fault diagnosis via self-organized neural-symbolic nodes
Qi Li, Lichang Qin, Haifeng Xu, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103156-103156
Closed Access
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