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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 new dynamic model and transfer learning based intelligent fault diagnosis framework for rolling element bearings race faults: Solving the small sample problem
Yunjia Dong, Yuqing Li, Huailiang Zheng, et al.
ISA Transactions (2021) Vol. 121, pp. 327-348
Closed Access | Times Cited: 149

Showing 1-25 of 149 citing articles:

Deep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016
Xiaohan Chen, Rui Yang, Yihao Xue, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-21
Open Access | Times Cited: 185
Meta-learning as a promising approach for few-shot cross-domain fault diagnosis: Algorithms, applications, and prospects
Yong Feng, Jinglong Chen, Jingsong Xie, et al.
Knowledge-Based Systems (2021) Vol. 235, pp. 107646-107646
Closed Access | Times Cited: 164
Fault diagnosis for small samples based on attention mechanism
Xin Zhang, Chao He, Yanping Lu, et al.
Measurement (2021) Vol. 187, pp. 110242-110242
Closed Access | Times Cited: 140
A Calibration-Based Hybrid Transfer Learning Framework for RUL Prediction of Rolling Bearing Across Different Machines
Yafei Deng, Shichang Du, Dong Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-15
Closed Access | Times Cited: 86
Meta-learning approaches for learning-to-learn in deep learning: A survey
Yingjie Tian, Xiaoxi Zhao, Wei Huang
Neurocomputing (2022) Vol. 494, pp. 203-223
Closed Access | Times Cited: 79
A survey of transfer learning for machinery diagnostics and prognostics
Siya Yao, Qi Kang, MengChu Zhou, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 4, pp. 2871-2922
Closed Access | Times Cited: 74
A bearing fault diagnosis method without fault data in new working condition combined dynamic model with deep learning
Kun Xu, Xianguang Kong, Qibin Wang, et al.
Advanced Engineering Informatics (2022) Vol. 54, pp. 101795-101795
Closed Access | Times Cited: 68
Transfer Learning-Motivated Intelligent Fault Diagnosis Designs: A Survey, Insights, and Perspectives
Hongtian Chen, Hao Luo, Biao Huang, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 3, pp. 2969-2983
Open Access | Times Cited: 61
Deep causal factorization network: A novel domain generalization method for cross-machine bearing fault diagnosis
Sixiang Jia, Yongbo Li, Xinyue Wang, et al.
Mechanical Systems and Signal Processing (2023) Vol. 192, pp. 110228-110228
Closed Access | Times Cited: 49
Digital twin-assisted enhanced meta-transfer learning for rolling bearing fault diagnosis
Leiming Ma, Bin Jiang, Lingfei Xiao, et al.
Mechanical Systems and Signal Processing (2023) Vol. 200, pp. 110490-110490
Closed Access | Times Cited: 43
A Systematic Literature Review on Transfer Learning for Predictive Maintenance in Industry 4.0
Mehdi Saman Azari, Francesco Flammini, Stefania Santini, et al.
IEEE Access (2023) Vol. 11, pp. 12887-12910
Open Access | Times Cited: 42
Deep transfer learning strategy in intelligent fault diagnosis of rotating machinery
Shengnan Tang, Jingtao Ma, Zhengqi Yan, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108678-108678
Closed Access | Times Cited: 27
A residual denoising and multiscale attention-based weighted domain adaptation network for tunnel boring machine main bearing fault diagnosis
Zhong Tao, Chengjin Qin, Gang Shi, et al.
Science China Technological Sciences (2024) Vol. 67, Iss. 8, pp. 2594-2618
Closed Access | Times Cited: 18
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
Dynamic weighted adversarial domain adaptation network with sparse representation denoising module for rotating machinery fault diagnosis
Maogui Niu, Hongkai Jiang, Haidong Shao
Engineering Applications of Artificial Intelligence (2025) Vol. 142, pp. 109963-109963
Closed Access | Times Cited: 2
Multi-perspective deep transfer learning model: A promising tool for bearing intelligent fault diagnosis under varying working conditions
Xue‐Gang Li, Xingxing Jiang, Qian Wang, et al.
Knowledge-Based Systems (2022) Vol. 243, pp. 108443-108443
Closed Access | Times Cited: 38
Deep Transfer Learning Models for Industrial Fault Diagnosis Using Vibration and Acoustic Sensors Data: A Review
Md Roman Bhuiyan, Jia Uddin
Vibration (2023) Vol. 6, Iss. 1, pp. 218-238
Open Access | Times Cited: 38
Research on rolling bearing virtual-real fusion life prediction with digital twin
Wentao Zhao, Chao Zhang, Bin Fan, et al.
Mechanical Systems and Signal Processing (2023) Vol. 198, pp. 110434-110434
Open Access | Times Cited: 35
Semi-supervised multi-sensor information fusion tailored graph embedded low-rank tensor learning machine under extremely low labeled rate
Haifeng Xu, Xu Wang, Jinfeng Huang, et al.
Information Fusion (2023) Vol. 105, pp. 102222-102222
Closed Access | Times Cited: 31
A new bearing fault diagnosis method via simulation data driving transfer learning without target fault data
Wenbo Hou, Chunlin Zhang, Yunqian Jiang, et al.
Measurement (2023) Vol. 215, pp. 112879-112879
Closed Access | Times Cited: 30
Simulation-Driven Subdomain Adaptation Network for bearing fault diagnosis with missing samples
Jianing Liu, Hongrui Cao, Shuaiming Su, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106201-106201
Closed Access | Times Cited: 29
Intelligent fault diagnosis of bearings under small samples: A mechanism-data fusion approach
Kun Xu, Xianguang Kong, Qibin Wang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107063-107063
Closed Access | Times Cited: 29
Remaining useful life prediction combined dynamic model with transfer learning under insufficient degradation data
Han Cheng, Xianguang Kong, Qibin Wang, et al.
Reliability Engineering & System Safety (2023) Vol. 236, pp. 109292-109292
Closed Access | Times Cited: 26
Fault diagnosis of gearbox driven by vibration response mechanism and enhanced unsupervised domain adaptation
Fei Jiang, Weiqi Lin, Zhaoqian Wu, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102460-102460
Closed Access | Times Cited: 13
Gearbox fault diagnosis method based on lightweight channel attention mechanism and transfer learning
Xuemin Cheng, Shuihai Dou, Yanping Du, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
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