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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:

Intelligent fault diagnosis of rolling bearings under varying operating conditions based on domain-adversarial neural network and attention mechanism
Hao Wu, Jimeng Li, Qingyu Zhang, et al.
ISA Transactions (2022) Vol. 130, pp. 477-489
Closed Access | Times Cited: 62

Showing 1-25 of 62 citing articles:

Attention mechanism in intelligent fault diagnosis of machinery: A review of technique and application
Haixin Lv, Jinglong Chen, Tongyang Pan, et al.
Measurement (2022) Vol. 199, pp. 111594-111594
Closed Access | Times Cited: 148
An improved GNN using dynamic graph embedding mechanism: A novel end-to-end framework for rolling bearing fault diagnosis under variable working conditions
Zidong Yu, Changhe Zhang, Chao Deng
Mechanical Systems and Signal Processing (2023) Vol. 200, pp. 110534-110534
Closed Access | Times Cited: 54
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
An efficient lightweight neural network using BiLSTM-SCN-CBAM with PCA-ICEEMDAN for diagnosing rolling bearing faults
You Keshun, Guangqi Qiu, Yingkui Gu
Measurement Science and Technology (2023) Vol. 34, Iss. 9, pp. 094001-094001
Closed Access | Times Cited: 41
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
Rolling Bearing Fault Diagnosis Using Hybrid Neural Network with Principal Component Analysis
You Keshun, Guangqi Qiu, Yingkui Gu
Sensors (2022) Vol. 22, Iss. 22, pp. 8906-8906
Open Access | Times Cited: 46
Triplet attention-enhanced residual tree-inspired decision network: A hierarchical fault diagnosis model for unbalanced bearing datasets
Lingli Cui, Zhilin Dong, Hai Xu, et al.
Advanced Engineering Informatics (2023) Vol. 59, pp. 102322-102322
Closed Access | Times Cited: 32
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
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
Transfer learning rolling bearing fault diagnosis model based on deep feature decomposition and class-level alignment
Jingchuan Dong, Hongyu Jiang, Depeng Su, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 4, pp. 046006-046006
Closed Access | Times Cited: 8
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
Multi-source domain adaptive network based on local kernelized higher-order moment matching for rotating machinery fault diagnosis
Ying Zhang, Jingjing Fan, Zong Meng, et al.
ISA Transactions (2024) Vol. 150, pp. 311-321
Closed Access | Times Cited: 5
A WOA-SVMD and multi-scale CNN-transformer method for fault diagnosis of motor bearing
Zejiang Xu, Jili Tao, Y. Hu, et al.
Measurement and Control (2025)
Open Access
Self-supervised learning-based dual-classifier domain adaptation model for rolling bearings cross-domain fault diagnosis
Quan Jiang, Xiaoshan Lin, Xingchi Lu, et al.
Knowledge-Based Systems (2023) Vol. 284, pp. 111229-111229
Closed Access | Times Cited: 14
Intelligent Diagnosis of Dual-Channel Parallel Rolling Bearings Based on Feature Fusion
Haike Guo, Xiaoqiang Zhao
IEEE Sensors Journal (2024) Vol. 24, Iss. 7, pp. 10640-10655
Closed Access | Times Cited: 4
Bearing fault diagnosis based on high-confidence pseudo-labels and dual-view multi-adversarial sparse joint attention network under variable working conditions
Cailu Pan, Zhiwu Shang, Wanxiang Li, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108625-108625
Closed Access | Times Cited: 4
A zero-shot model for diagnosing unknown composite faults in train bearings based on label feature vector generated fault features
Deqiang He, Yuan Xu, Zhenzhen Jin, et al.
Applied Acoustics (2025) Vol. 232, pp. 110563-110563
Closed Access
A GraphKAN-Based Intelligent Fault Diagnosis Method of Rolling Bearing Under Variable Working Conditions
Ye Liu, Yanhe Xu, Jie Liu, et al.
Symmetry (2025) Vol. 17, Iss. 2, pp. 241-241
Open Access
A hierarchical adversarial multi-target domain adaptation for gear fault diagnosis under variable working condition based on raw acoustic signal
Yong Yao, Qiuyi Chen, Gui Gui, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106449-106449
Closed Access | Times Cited: 11
Bearing fault diagnosis using Gradual Conditional Domain Adversarial Network
Chu‐ge Wu, Duo Zhao, Te Han, et al.
Applied Soft Computing (2024) Vol. 158, pp. 111580-111580
Closed Access | Times Cited: 3
Federated Transfer Learning-Based Distributed Fault Diagnosis Method for Rolling Bearings
Guang Yang, Juan Su, Songhuai Du, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 12, pp. 126111-126111
Closed Access | Times Cited: 3
Deep Adversarial Hybrid Domain-Adaptation Network for Varying Working Conditions Fault Diagnosis of High-Speed Train Bogie
Buyao Yang, Tiantian Wang, Jingsong Xie, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-10
Closed Access | Times Cited: 10
Adversarial Deep Transfer Learning in Fault Diagnosis: Progress, Challenges, and Future Prospects
Yu Guo, Jundong Zhang, Bin Sun, et al.
Sensors (2023) Vol. 23, Iss. 16, pp. 7263-7263
Open Access | Times Cited: 9
An Adversarial Single-Domain Generalization Network for Fault Diagnosis of Wind Turbine Gearboxes
Xinran Wang, Chenyong Wang, Hanlin Liu, et al.
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 12, pp. 2384-2384
Open Access | Times Cited: 9
A novel algorithm for complex transfer conditions in bearing fault diagnosis
Jingchuan Dong, Depeng Su, Hongyu Jiang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 5, pp. 056118-056118
Closed Access | Times Cited: 3
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