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:

Semi-supervised multi-scale attention-aware graph convolution network for intelligent fault diagnosis of machine under extremely-limited labeled samples
Zongliang Xie, Jinglong Chen, Yong Feng, et al.
Journal of Manufacturing Systems (2022) Vol. 64, pp. 561-577
Closed Access | Times Cited: 62

Showing 51-75 of 62 citing articles:

IGFT-MHCNN: An intelligent diagnostic model for motor compound faults based decoupling and denoising of multi-source vibration signals
Xiaoyun Gong, Zeheng Zhi, Yiyuan Gao, et al.
Journal of Vibration and Control (2024)
Closed Access

Application of symmetric uncertainty and emperor penguin–grey wolf optimisation for feature selection in motor fault classification
Chun‐Yao Lee, Truong‐An Le, Wei‐Lun Chien, et al.
IET Electric Power Applications (2024) Vol. 18, Iss. 10, pp. 1107-1121
Open Access

Lightweight pyramid attention residual network for intelligent fault diagnosis of machine under sharp speed variation
Zongliang Xie, Jinglong Chen, Zhen Shi, et al.
Mechanical Systems and Signal Processing (2024) Vol. 223, pp. 111824-111824
Closed Access

A Semi-supervised Intelligent Fault Diagnosis Method for Bearings under Low Labeled Rates
Tianyi Ye, Xianfeng Yuan, Xilin Yang, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-11
Closed Access

Data-driven unsupervised anomaly detection of manufacturing processes with multi-scale prototype augmentation and multi-sensor data
Zongliang Xie, Zhipeng Zhang, Jinglong Chen, et al.
Journal of Manufacturing Systems (2024) Vol. 77, pp. 26-39
Closed Access

Current signal analysis using SW-GAT networks for fault diagnosis of electromechanical drive systems under extreme data imbalance
Chaoge Wang, Xinyu Tian, Feng Zhou, et al.
Measurement Science and Technology (2024) Vol. 36, Iss. 1, pp. 016140-016140
Closed Access

Few-Shot Graph Neural Networks Framework Incorporating DGAT for Planetary Gearbox Diagnosis
Jia Gao, Peng Chen, Yao Jin, et al.
Mechanisms and machine science (2024), pp. 372-384
Closed Access

Bearing fault diagnosis for variable working conditions via lightweight transformer and homogeneous generalized contrastive learning with inter-class repulsive discriminant
Qiang Zhou, Wengang Ma, Yadong Zhang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 139, pp. 109548-109548
Closed Access

DSTF-Net: A Novel Framework for Intelligent Diagnosis of Insulated Bearings in Wind Turbines with Multi-Source Data and Its Interpretability
Tongguang Yang, Ming Xu, Chun‐Lung Chen, et al.
Renewable Energy (2024), pp. 121965-121965
Closed Access

A two-stage health prognostics with spatiotemporal feature representation and uncertainty quantification for bearings
Donghui Pan, Yongkang Liu, Yantao Wei, et al.
Expert Systems with Applications (2024), pp. 126111-126111
Closed Access

Fault diagnosis for spent fuel shearing machines based on Bayesian optimization and CBAM-ResNet
Pingping Wang, Jia−Hua Chen, Zelin Wang, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 2, pp. 025901-025901
Closed Access | Times Cited: 1

A review of bearing fault diagnosis based on weakly supervised learning
Bichuang Zhao, Jian Cen, Weiwei Si, et al.
2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (SAFEPROCESS) (2023) Vol. 70, pp. 1-9
Closed Access

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