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:
Enhancing Intelligent Cross-Domain Fault Diagnosis Performance on Rotating Machines with Noisy Health Labels
Abhijeet Ainapure, Xiang Li, Jaskaran Singh, et al.
Procedia Manufacturing (2020) Vol. 48, pp. 940-946
Open Access | Times Cited: 13
Abhijeet Ainapure, Xiang Li, Jaskaran Singh, et al.
Procedia Manufacturing (2020) Vol. 48, pp. 940-946
Open Access | Times Cited: 13
Showing 13 citing articles:
A fault diagnosis method for wind turbines gearbox based on adaptive loss weighted meta-ResNet under noisy labels
Kai Zhang, Baoping Tang, Lei Deng, et al.
Mechanical Systems and Signal Processing (2021) Vol. 161, pp. 107963-107963
Closed Access | Times Cited: 111
Kai Zhang, Baoping Tang, Lei Deng, et al.
Mechanical Systems and Signal Processing (2021) Vol. 161, pp. 107963-107963
Closed Access | Times Cited: 111
A systematic literature review of deep learning for vibration-based fault diagnosis of critical rotating machinery: Limitations and challenges
Omri Matania, Itai Dattner, Jacob Bortman, et al.
Journal of Sound and Vibration (2024) Vol. 590, pp. 118562-118562
Closed Access | Times Cited: 16
Omri Matania, Itai Dattner, Jacob Bortman, et al.
Journal of Sound and Vibration (2024) Vol. 590, pp. 118562-118562
Closed Access | Times Cited: 16
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: 75
Siyu Zhang, Lei Su, Jiefei Gu, et al.
Chinese Journal of Aeronautics (2021) Vol. 36, Iss. 1, pp. 45-74
Open Access | Times Cited: 75
Deep Transfer Learning in Mechanical Intelligent Fault Diagnosis: Application and Challenge
Chenhui Qian, Junjun Zhu, Yehu Shen, et al.
Neural Processing Letters (2022) Vol. 54, Iss. 3, pp. 2509-2531
Closed Access | Times Cited: 58
Chenhui Qian, Junjun Zhu, Yehu Shen, et al.
Neural Processing Letters (2022) Vol. 54, Iss. 3, pp. 2509-2531
Closed Access | Times Cited: 58
An intelligent fault diagnosis method for rolling bearings based on feature transfer with improved DenseNet and joint distribution adaptation
Chenhui Qian, Quan Jiang, Yehu Shen, et al.
Measurement Science and Technology (2021) Vol. 33, Iss. 2, pp. 025101-025101
Closed Access | Times Cited: 34
Chenhui Qian, Quan Jiang, Yehu Shen, et al.
Measurement Science and Technology (2021) Vol. 33, Iss. 2, pp. 025101-025101
Closed Access | Times Cited: 34
Multi-model ensemble deep learning method for intelligent fault diagnosis with high-dimensional samples
Xin Zhang, Tao Huang, Bo Wu, et al.
Frontiers of Mechanical Engineering (2021) Vol. 16, Iss. 2, pp. 340-352
Closed Access | Times Cited: 33
Xin Zhang, Tao Huang, Bo Wu, et al.
Frontiers of Mechanical Engineering (2021) Vol. 16, Iss. 2, pp. 340-352
Closed Access | Times Cited: 33
A Tensor-based domain alignment method for intelligent fault diagnosis of rolling bearing in rotating machinery
Zhaohua Liu, Liang Chen, Hua‐Liang Wei, et al.
Reliability Engineering & System Safety (2022) Vol. 230, pp. 108968-108968
Open Access | Times Cited: 19
Zhaohua Liu, Liang Chen, Hua‐Liang Wei, et al.
Reliability Engineering & System Safety (2022) Vol. 230, pp. 108968-108968
Open Access | Times Cited: 19
A transfer learning method: Universal domain adaptation with noisy samples for bearing fault diagnosis
Yi Sun, Hong‐Liang Song, Liang Guo, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103243-103243
Closed Access
Yi Sun, Hong‐Liang Song, Liang Guo, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103243-103243
Closed Access
Intelligent Robust Cross-Domain Fault Diagnostic Method for Rotating Machines Using Noisy Condition Labels
Abhijeet Ainapure, Shahin Siahpour, Xiang Li, et al.
Mathematics (2022) Vol. 10, Iss. 3, pp. 455-455
Open Access | Times Cited: 12
Abhijeet Ainapure, Shahin Siahpour, Xiang Li, et al.
Mathematics (2022) Vol. 10, Iss. 3, pp. 455-455
Open Access | Times Cited: 12
Recent advances in data-driven dynamics and control
Zhi-Sai Ma, Xiang Li, Meng-Xin He, et al.
International Journal of Dynamics and Control (2020) Vol. 8, Iss. 4, pp. 1200-1221
Closed Access | Times Cited: 9
Zhi-Sai Ma, Xiang Li, Meng-Xin He, et al.
International Journal of Dynamics and Control (2020) Vol. 8, Iss. 4, pp. 1200-1221
Closed Access | Times Cited: 9
Research on bearing vibration signal generation method based on filtering WGAN_GP with small samples
Jiesong Li, Tao Liu, Xing Wu
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science (2023) Vol. 237, Iss. 20, pp. 4911-4929
Closed Access | Times Cited: 3
Jiesong Li, Tao Liu, Xing Wu
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science (2023) Vol. 237, Iss. 20, pp. 4911-4929
Closed Access | Times Cited: 3
Active label-denoising algorithm based on broad learning for annotation of machine health status
GuoKai Liu, Weiming Shen, Liang Gao, et al.
Science China Technological Sciences (2022) Vol. 65, Iss. 9, pp. 2089-2104
Closed Access | Times Cited: 4
GuoKai Liu, Weiming Shen, Liang Gao, et al.
Science China Technological Sciences (2022) Vol. 65, Iss. 9, pp. 2089-2104
Closed Access | Times Cited: 4
Imbalanced fault diagnosis of rolling bearing using a deep gradient improved generative adversarial network
Shaowei Liu, Hongkai Jiang, Zhenghong Wu, et al.
(2022) Vol. 13, pp. 127-132
Closed Access | Times Cited: 3
Shaowei Liu, Hongkai Jiang, Zhenghong Wu, et al.
(2022) Vol. 13, pp. 127-132
Closed Access | Times Cited: 3
