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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 multi-source information transfer learning method with subdomain adaptation for cross-domain fault diagnosis
Jinghui Tian, Dongying Han, Mengdi Li, et al.
Knowledge-Based Systems (2022) Vol. 243, pp. 108466-108466
Closed Access | Times Cited: 113

Showing 1-25 of 113 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
A multi-source domain information fusion network for rotating machinery fault diagnosis under variable operating conditions
Tianyu Gao, Jingli Yang, Qing Tang
Information Fusion (2024) Vol. 106, pp. 102278-102278
Closed Access | Times Cited: 46
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 learning-based open set multi-source domain adaptation with complementary transferability metric for mechanical fault diagnosis
Jinghui Tian, Dongying Han, Hamid Reza Karimi, et al.
Neural Networks (2023) Vol. 162, pp. 69-82
Closed Access | Times Cited: 40
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 new multi-source information domain adaption network based on domain attributes and features transfer for cross-domain fault diagnosis
Yue Yu, Hamid Reza Karimi, Peiming Shi, et al.
Mechanical Systems and Signal Processing (2024) Vol. 211, pp. 111194-111194
Open Access | Times Cited: 20
Self-paced decentralized federated transfer framework for rotating machinery fault diagnosis with multiple domains
Ke Zhao, Zhenbao Liu, Jia Li, et al.
Mechanical Systems and Signal Processing (2024) Vol. 211, pp. 111258-111258
Closed Access | Times Cited: 16
A new adaptive multi-scale attention adversarial network for cross-domain fault diagnosis
Lingtan Kong, Jinrui Wang, Dawei Wang, et al.
Knowledge-Based Systems (2025), pp. 113066-113066
Closed Access | Times Cited: 1
Modified DSAN for unsupervised cross-domain fault diagnosis of bearing under speed fluctuation
Jingjie Luo, Haidong Shao, Hongru Cao, et al.
Journal of Manufacturing Systems (2022) Vol. 65, pp. 180-191
Open Access | Times Cited: 45
Remaining useful life prediction based on transfer multi-stage shrinkage attention temporal convolutional network under variable working conditions
Wanxiang Li, Zhiwu Shang, Maosheng Gao, et al.
Reliability Engineering & System Safety (2022) Vol. 226, pp. 108722-108722
Closed Access | Times Cited: 40
Multi-source weighted source-free domain transfer method for rotating machinery fault diagnosis
Qinhe Gao, Tong Huang, Ke Zhao, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121585-121585
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
Domain adaptation meta-learning network with discard-supplement module for few-shot cross-domain rotating machinery fault diagnosis
Yu Zhang, Dongying Han, Jinghui Tian, et al.
Knowledge-Based Systems (2023) Vol. 268, pp. 110484-110484
Closed Access | Times Cited: 28
Multiple Source-Free Domain Adaptation Network Based on Knowledge Distillation for Machinery Fault Diagnosis
Ke Yue, Jipu Li, Zhuyun Chen, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-11
Closed Access | Times Cited: 21
Intelligent diagnosis method for machine faults based on federated transfer learning
Li Zhi, Zedong Li, Fengshou Gu
Applied Soft Computing (2024) Vol. 163, pp. 111922-111922
Closed Access | Times Cited: 13
Cross-Supervised multisource prototypical network: A novel domain adaptation method for multi-source few-shot fault diagnosis
Xiao Zhang, Weiguo Huang, Chuancang Ding, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102538-102538
Closed Access | Times Cited: 12
Curriculum learning-based domain generalization for cross-domain fault diagnosis with category shift
Yu Wang, Jie Gao, Wei Wang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 212, pp. 111295-111295
Closed Access | Times Cited: 9
A universal multi-source domain adaptation method with unsupervised clustering for mechanical fault diagnosis under incomplete data
Jinghui Tian, Dongying Han, Hamid Reza Karimi, et al.
Neural Networks (2024) Vol. 173, pp. 106167-106167
Closed Access | Times Cited: 7
A reliable feature-assisted contrastive generalization net for intelligent fault diagnosis under unseen machines and working conditions
Zhen Shi, Jinglong Chen, Xinwei Zhang, et al.
Mechanical Systems and Signal Processing (2022) Vol. 188, pp. 110011-110011
Closed Access | Times Cited: 32
Transferable graph features-driven cross-domain rotating machinery fault diagnosis
Chaoying Yang, Jie Liu, Kaibo Zhou, et al.
Knowledge-Based Systems (2022) Vol. 250, pp. 109069-109069
Closed Access | Times Cited: 31
A Multisource Domain Adaptation Network for Process Fault Diagnosis Under Different Working Conditions
Shijin Li, Jianbo Yu
IEEE Transactions on Industrial Electronics (2022) Vol. 70, Iss. 6, pp. 6272-6283
Closed Access | Times Cited: 30
A novel Brownian correlation metric prototypical network for rotating machinery fault diagnosis with few and zero shot learners
Jingli Yang, Changdong Wang, Changan Wei
Advanced Engineering Informatics (2022) Vol. 54, pp. 101815-101815
Closed Access | Times Cited: 30
A new intelligent fault diagnosis framework for rotating machinery based on deep transfer reinforcement learning
Daoguang Yang, Hamid Reza Karimi, Marek Pawełczyk
Control Engineering Practice (2023) Vol. 134, pp. 105475-105475
Open Access | Times Cited: 20
Multi-source partial domain adaptation method based on pseudo-balanced target domain for fault diagnosis
Guowei Zhang, Xianguang Kong, Qibin Wang, et al.
Knowledge-Based Systems (2023) Vol. 284, pp. 111255-111255
Closed Access | Times Cited: 16
Semi-supervised prototype network based on compact-uniform-sparse representation for rotating machinery few-shot class incremental fault diagnosis
Yu Zhang, Dongying Han, Peiming Shi
Expert Systems with Applications (2024) Vol. 255, pp. 124660-124660
Closed Access | Times Cited: 7
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