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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-augmented patch variational autoencoding generative adversarial networks for rolling bearing fault diagnosis
Xin Wang, Hongkai Jiang, Yunpeng Liu, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 5, pp. 055102-055102
Closed Access | Times Cited: 19

Showing 19 citing articles:

A review on deep learning in planetary gearbox health state recognition: methods, applications, and dataset publication
Dongdong Liu, Lingli Cui, Weidong Cheng
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 012002-012002
Closed Access | Times Cited: 81
A trackable multi-domain collaborative generative adversarial network for rotating machinery fault diagnosis
Xin Wang, Hongkai Jiang, Mingzhe Mu, et al.
Mechanical Systems and Signal Processing (2024) Vol. 224, pp. 111950-111950
Closed Access | Times Cited: 31
Conditional distribution-guided adversarial transfer learning network with multi-source domains for rolling bearing fault diagnosis
Zhenghong Wu, Hongkai Jiang, Shaowei Liu, et al.
Advanced Engineering Informatics (2023) Vol. 56, pp. 101993-101993
Closed Access | Times Cited: 30
A review: the application of generative adversarial network for mechanical fault diagnosis
Weiqing Liao, Ke Yang, Wenlong Fu, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 062002-062002
Closed Access | Times Cited: 7
Research of turbine rotor fault diagnosis based on improved auxiliary classification generative adversarial network
Qinglei Zhang, Xinwei Lian, Jiyun Qin, et al.
Measurement (2025), pp. 116991-116991
Closed Access
Remaining Useful Life Prediction Method Enhanced by Data Augmentation and Similarity Fusion
Huaqing Wang, Ye Li, Ye Jin, et al.
Vibration (2024) Vol. 7, Iss. 2, pp. 560-581
Open Access | Times Cited: 2
Bearing fault detection system based on a deep diffusion model
Her‐Terng Yau, Ping‐Huan Kuo, S. Yu
Structural Health Monitoring (2024)
Closed Access | Times Cited: 2
Rolling bearing fault diagnosis method based on dynamic simulated model from source domain to target domain with improved alternating transfer learning
Heng Wang, Peng Wang, Siyuan Wang, et al.
Nonlinear Dynamics (2024)
Closed Access | Times Cited: 2
Construction Method of a Digital-Twin Simulation System for SCARA Robots Based on Modular Communication
Zihan Zhang, Qihui Guo, М. А. Григорьев, et al.
Sensors (2024) Vol. 24, Iss. 22, pp. 7183-7183
Open Access | Times Cited: 2
Degradation trend feature generation improved rotating machines RUL prognosis method with limited run-to-failure data
Kai Zhang, Yantao Liu, Yisheng Zou, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 7, pp. 075019-075019
Closed Access | Times Cited: 6
CMAGAN: classifier-aided minority augmentation generative adversarial networks for industrial imbalanced data and its application to fault prediction
Wenjie Wang, Zhao Liu, Ping Zhu
Advances in Manufacturing (2024) Vol. 12, Iss. 3, pp. 603-618
Closed 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
Review of imbalanced fault diagnosis technology based on generative adversarial networks
Hualin Chen, Jianan Wei, Haisong Huang, et al.
Journal of Computational Design and Engineering (2024) Vol. 11, Iss. 5, pp. 99-124
Open Access | Times Cited: 1
Fault detection of a reciprocating plunger pump with fault-free data based on an unsupervised feature encoder and minimum covariance determinant
Yuehua Lai, Ran Li, Yang Zhang, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 10, pp. 105115-105115
Closed Access | Times Cited: 2
An enhanced meta-learning network with sensitivity penalty for cross-domain few-shot fault diagnosis
Mingzhe Mu, Hongkai Jiang, Wenxin Jiang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 9, pp. 095106-095106
Closed Access
Optimal transport strategy-based meta-attention network for fault diagnosis of rotating machinery with zero sample
Ke Wu, Kaiwei Yu, Chong Chen, et al.
Applied Intelligence (2024) Vol. 54, Iss. 9-10, pp. 6799-6815
Closed Access
Research on Rolling Bearing Fault Diagnosis Method Based on Simulation Source Domain to Experimental Target Domain with Improved Alternating Transfer Learning
Heng Wang, Peng Wang, Siyuan Wang, et al.
Research Square (Research Square) (2024)
Closed Access
Generation of high-dimensional vibration signal and its application in fault diagnosis
Zhijun Ren, Dawei Gao, Yongsheng Zhu, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 015103-015103
Closed Access | Times Cited: 1
GIS partial discharge data enhancement method based on self attention mechanism VAE-GAN
Qinglin Qian, Weihao Sun, Zhen Wang, et al.
Global Energy Interconnection (2023) Vol. 6, Iss. 5, pp. 601-613
Open Access | Times Cited: 1
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