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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:

A unified framework incorporating predictive generative denoising autoencoder and deep Coral network for rolling bearing fault diagnosis with unbalanced data
Xingqiu Li, Hongkai Jiang, Shaowei Liu, et al.
Measurement (2021) Vol. 178, pp. 109345-109345
Closed Access | Times Cited: 46

Showing 1-25 of 46 citing articles:

A Systematic Review on Imbalanced Learning Methods in Intelligent Fault Diagnosis
Zhijun Ren, Tantao Lin, Ke Feng, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-35
Closed Access | Times Cited: 87
Single and simultaneous fault diagnosis of gearbox via wavelet transform and improved deep residual network under imbalanced data
Suiyan Wang, Jiaye Tian, Pengfei Liang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108146-108146
Closed Access | Times Cited: 40
An integrated deep multiscale feature fusion network for aeroengine remaining useful life prediction with multisensor data
Xingqiu Li, Hongkai Jiang, Yuan Liu, et al.
Knowledge-Based Systems (2021) Vol. 235, pp. 107652-107652
Closed Access | Times Cited: 73
Rotating machinery fault detection and diagnosis based on deep domain adaptation: A survey
Siyu Zhang, Lei Su, Jiefei Gu, et al.
Chinese Journal of Aeronautics (2021) Vol. 36, Iss. 1, pp. 45-74
Open Access | Times Cited: 73
Interpretable domain adaptation transformer: a transfer learning method for fault diagnosis of rotating machinery
Dongdong Liu, Lingli Cui, Gang Wang, et al.
Structural Health Monitoring (2024)
Closed Access | Times Cited: 13
Generative artificial intelligence and data augmentation for prognostic and health management: Taxonomy, progress, and prospects
Shen Liu, Jinglong Chen, Yong Feng, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124511-124511
Closed Access | Times Cited: 8
A new data generation approach with modified Wasserstein auto-encoder for rotating machinery fault diagnosis with limited fault data
Ke Zhao, Hongkai Jiang, Chaoqiang Liu, et al.
Knowledge-Based Systems (2021) Vol. 238, pp. 107892-107892
Closed Access | Times Cited: 42
Imbalance fault diagnosis under long-tailed distribution: Challenges, solutions and prospects
Zhuohang Chen, Jinglong Chen, Yong Feng, et al.
Knowledge-Based Systems (2022) Vol. 258, pp. 110008-110008
Closed Access | Times Cited: 35
A graph neural network-based bearing fault detection method
Xiaoxia Lü, Xiaoxin Yang, Xiaodong Yang
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 20
A novel sample selection approach based universal unsupervised domain adaptation for fault diagnosis of rotating machinery
Biliang Lu, Yingjie Zhang, Zhaohua Liu, et al.
Reliability Engineering & System Safety (2023) Vol. 240, pp. 109618-109618
Closed Access | Times Cited: 18
Dual Weighted-Class Adversarial Network for Rotary Machine Fault Diagnosis Using Multisource Domain with Class-Inconsistent Data
Shengkang Yang, Boyang Lei, Qibin Wang, et al.
IEEE/ASME Transactions on Mechatronics (2024) Vol. 29, Iss. 5, pp. 3473-3484
Closed Access | Times Cited: 6
Domain adaptation with domain specific information and feature disentanglement for bearing fault diagnosis
Shaozhang Xie, Peng Xia, Hanqi Zhang
Measurement Science and Technology (2024) Vol. 35, Iss. 5, pp. 056101-056101
Open Access | Times Cited: 5
Fusion-Based Dual-Task Architecture for Predicting the Remaining Useful Life of an Aeroengine
Xiao Zhong Du, Jiajie Chen, Jiqiang Wang, et al.
Journal of Aerospace Engineering (2025) Vol. 38, Iss. 3
Closed Access
Data-driven machinery fault diagnosis: A comprehensive review
Dhiraj Neupane, Mohamed Reda Bouadjenek, Richard Dazeley, et al.
Neurocomputing (2025), pp. 129588-129588
Open Access
A Fault Diagnosis Method for Marine Engine Cross Working Conditions Based on Transfer Learning
Long-De Wang, Hui Cao, Zhichao Cui, et al.
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 2, pp. 270-270
Open Access | Times Cited: 4
Domain reinforcement feature adaptation methodology with correlation alignment for compound fault diagnosis of rolling bearing
Zisheng Wang, Jianping Xuan, Tielin Shi
Expert Systems with Applications (2024), pp. 125594-125594
Closed Access | Times Cited: 4
A robust multi-scale learning network with quasi-hyperbolic momentum-based Adam optimizer for bearing intelligent fault diagnosis under sample imbalance scenarios and strong noise environment
Maoyou Ye, Xiaoan Yan, Ning Chen, et al.
Structural Health Monitoring (2023) Vol. 23, Iss. 3, pp. 1664-1686
Closed Access | Times Cited: 12
Applications of Artificial Intelligence for Fault Diagnosis of Rotating Machines: A Review
Fasikaw Kibrete, Dereje Engida Woldemichael
(2023), pp. 41-62
Closed Access | Times Cited: 9
Domain generalized open-set intelligent fault diagnosis based on feature disentanglement meta-learning
Xiangdong Zhou, Deng Xiao, Zhengwu Liu, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 11, pp. 115001-115001
Closed Access | Times Cited: 3
A novel joint distinct subspace learning and dynamic distribution adaptation method for fault transfer diagnosis
Huoyao Xu, Junlang Wang, Jie Liu, et al.
Measurement (2022) Vol. 203, pp. 111986-111986
Closed Access | Times Cited: 15
A Novel Semi-Supervised Graph-Guided Approach for Intelligent Health State Diagnosis of a 3-PRR Planar Parallel Manipulator
Bo Zhao, Xianmin Zhang, Zhenhui Zhan, et al.
IEEE/ASME Transactions on Mechatronics (2022) Vol. 27, Iss. 6, pp. 4786-4797
Closed Access | Times Cited: 12
A dual-weighted adversarial network for partial domain fault diagnosis of machinery
Xue Ding, Aidong Deng, Minqiang Deng, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 065108-065108
Closed Access | Times Cited: 2
Recent deep learning models for diagnosis and health monitoring: A review of research works and future challenges
Chuyue Lou, Mohamed Amine Atoui, Xiangshun Li
Transactions of the Institute of Measurement and Control (2023) Vol. 46, Iss. 14, pp. 2833-2870
Open Access | Times Cited: 6
KMSA-Net: A Knowledge-Mining-Based Semantic-Aware Network for Cross-Domain Industrial Process Fault Diagnosis
Lei Wang, Jinhai Liu, Huaguang Zhang, et al.
IEEE Transactions on Industrial Informatics (2023) Vol. 20, Iss. 2, pp. 2738-2750
Closed Access | Times Cited: 6
A novel transfer-learning method based on selective normalization for fault diagnosis with limited labeled data
Xiao Zhang, Baokun Han, Jinrui Wang, et al.
Measurement Science and Technology (2021) Vol. 32, Iss. 10, pp. 105116-105116
Closed Access | Times Cited: 14
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