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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.

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Showing 26-50 of 139 citing articles:

Attention gate guided multiscale recursive fusion strategy for deep neural network-based fault diagnosis
Zhiqiang Zhang, Funa Zhou, Hamid Reza Karimi, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107052-107052
Closed Access | Times Cited: 28
Wind turbines fault diagnosis method under variable working conditions based on AMVMD and deep discrimination transfer learning network
Peiming Shi, Linjie Jia, Siying Yi, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 4, pp. 046120-046120
Closed Access | Times Cited: 10
A review on convolutional neural network in rolling bearing fault diagnosis
Xin Li, Zengqiang Ma, Zonghao Yuan, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 7, pp. 072002-072002
Closed Access | Times Cited: 9
An Improved Deep Transfer Learning Method for Rotating Machinery Fault Diagnosis Based on Time Frequency Diagram and Pretraining Model
Liu Shao-qing, Z. Ji, Z. Zhang, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-12
Closed Access | Times Cited: 7
Adversarial domain adaptation with classifier alignment for cross-domain intelligent fault diagnosis of multiple source domains
Yongchao Zhang, Zhaohui Ren, Shihua Zhou, et al.
Measurement Science and Technology (2020) Vol. 32, Iss. 3, pp. 035102-035102
Closed Access | Times Cited: 50
Deep multi-scale separable convolutional network with triple attention mechanism: A novel multi-task domain adaptation method for intelligent fault diagnosis
Bo Zhao, Xianmin Zhang, Zhenhui Zhan, et al.
Expert Systems with Applications (2021) Vol. 182, pp. 115087-115087
Closed Access | Times Cited: 48
Research on rolling bearing fault diagnosis of small dataset based on a new optimal transfer learning network
Zhi Zheng, Jiuman Fu, Chuanqi Lu, et al.
Measurement (2021) Vol. 177, pp. 109285-109285
Closed Access | Times Cited: 43
Data augmentation for rolling bearing fault diagnosis using an enhanced few-shot Wasserstein auto-encoder with meta-learning
Zeyu Pei, Hongkai Jiang, Xingqiu Li, et al.
Measurement Science and Technology (2021) Vol. 32, Iss. 8, pp. 084007-084007
Closed Access | Times Cited: 42
Self-supervised bi-classifier adversarial transfer network for cross-domain fault diagnosis of rotating machinery
Jiachen Kuang, Guanghua Xu, Tangfei Tao, et al.
ISA Transactions (2022) Vol. 130, pp. 433-448
Closed Access | Times Cited: 34
A novel unsupervised directed hierarchical graph network with clustering representation for intelligent fault diagnosis of machines
Bo Zhao, Xianmin Zhang, Qiqiang Wu, et al.
Mechanical Systems and Signal Processing (2022) Vol. 183, pp. 109615-109615
Closed Access | Times Cited: 32
Multiscale dilated convolutional subdomain adaptation network with attention for unsupervised fault diagnosis of rotating machinery cross operating conditions
Yiming Xiao, Haidong Shao, Zhishan Min, et al.
Measurement (2022) Vol. 204, pp. 112146-112146
Closed Access | Times Cited: 32
The fault frequency priors fusion deep learning framework with application to fault diagnosis of offshore wind turbines
Tianming Xie, Qifa Xu, Cuixia Jiang, et al.
Renewable Energy (2022) Vol. 202, pp. 143-153
Closed Access | Times Cited: 29
A novel DL-BiGRU multi-feature fusion and deep transfer learning based modeling approach for quality prediction of injection molded products using small-sample datasets
Qingjie Qian, Junhe Yu, Hongfei Zhan, et al.
Journal of Manufacturing Processes (2024) Vol. 120, pp. 272-285
Closed Access | Times Cited: 6
Lightweight Knowledge Distillation-Based Transfer Learning Framework for Rolling Bearing Fault Diagnosis
Ruijia Lu, Shuzhi Liu, Zisu Gong, et al.
Sensors (2024) Vol. 24, Iss. 6, pp. 1758-1758
Open Access | Times Cited: 5
Bearing Fault Diagnosis for Cross-Condition Scenarios Under Data Scarcity Based on Transformer Transfer Learning Network
Miaoling Wu, Jun Jason Zhang, Peidong Xu, et al.
Electronics (2025) Vol. 14, Iss. 3, pp. 515-515
Open Access
Health Evaluation Techniques Towards Rotating Machinery: A Systematic Literature Review and Implementation Guideline
Weixiong Jiang, Jun Wu, Yifan Yang, et al.
Reliability Engineering & System Safety (2025) Vol. 260, pp. 110924-110924
Closed Access
A Semi-Supervised Deep Transfer Learning Approach for Rolling-Element Bearing Remaining Useful Life Prediction
Tarek Berghout, Leïla Hayet Mouss, Toufik Bentrcia, et al.
IEEE Transactions on Energy Conversion (2021) Vol. 37, Iss. 2, pp. 1200-1210
Closed Access | Times Cited: 32
A novel convolutional neural network with multiscale cascade midpoint residual for fault diagnosis of rolling bearings
Zhiqiang Chao, Tian Han
Neurocomputing (2022) Vol. 506, pp. 213-227
Closed Access | Times Cited: 22
MJAR: A novel joint generalization-based diagnosis method for industrial robots with compound faults
Yiming He, Chao Zhao, Xing Zhou, et al.
Robotics and Computer-Integrated Manufacturing (2023) Vol. 86, pp. 102668-102668
Closed Access | Times Cited: 15
A personalized federated learning-based fault diagnosis method for data suffering from network attacks
Zhiqiang Zhang, Funa Zhou, Chongsheng Zhang, et al.
Applied Intelligence (2023) Vol. 53, Iss. 19, pp. 22834-22849
Closed Access | Times Cited: 14
An Ensemble Domain Adaptation Network with High-quality Pseudo Labels for Rolling Bearing Fault Diagnosis
Ming Xie, Jianxin Liu, Yifan Li, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-10
Closed Access | Times Cited: 4
Multi-scale deep residual shrinkage networks with a hybrid attention mechanism for rolling bearing fault diagnosis
Xinliang Zhang, Yanqi Wang, Shengqiang Wei, et al.
Journal of Instrumentation (2024) Vol. 19, Iss. 05, pp. P05015-P05015
Open Access | Times Cited: 4
Optimized visual inertial SLAM for complex indoor dynamic scenes using RGB-D camera
Jiawei Chen, Wenchao Zhang, Dongyan Wei, et al.
Measurement (2025) Vol. 245, pp. 116615-116615
Closed Access
Deep Neural Network Ensemble for the Intelligent Fault Diagnosis of Machines Under Imbalanced Data
Feng Jia, Shihao Li, Hao Zuo, et al.
IEEE Access (2020) Vol. 8, pp. 120974-120982
Open Access | Times Cited: 34
A combination of residual and long–short-term memory networks for bearing fault diagnosis based on time-series model analysis
Youming Wang, Lin Cheng
Measurement Science and Technology (2020) Vol. 32, Iss. 1, pp. 015904-015904
Closed Access | Times Cited: 34

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