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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 progressive multi-source domain adaptation method for bearing fault diagnosis
Xiaorong Zheng, Zhiwei He, Jiahao Nie, et al.
Applied Acoustics (2023) Vol. 216, pp. 109797-109797
Closed Access | Times Cited: 10

Showing 10 citing articles:

EverAdapt: Continuous adaptation for dynamic machine fault diagnosis environments
Edward Edward, Mohamed Ragab, Mohamed Ragab, et al.
Mechanical Systems and Signal Processing (2025) Vol. 226, pp. 112317-112317
Closed Access
Source-free Progressive Domain Adaptation Network for Universal Cross-domain Fault Diagnosis of Industrial Equipment
Jipu Li, Ke Yue, Zhaoqian Wu, et al.
IEEE Sensors Journal (2025) Vol. 25, Iss. 5, pp. 8067-8078
Closed Access
Non-negative tensor factorization-based dependence map analysis for local damage detection in presence of non-Gaussian noise
Anna Michalak, Justyna Hebda-Sobkowicz, Anil Kumar, et al.
Measurement (2025), pp. 116840-116840
Closed Access
Enhancing robustness of cross machine fault diagnosis via an improved domain adversarial neural network and self-adversarial training
Bin Wang, Pengfei Liang, Lijie Zhang, et al.
Measurement (2025), pp. 117113-117113
Closed Access
A multi-branch attention coupled convolutional domain adaptation network for bearing intelligent fault recognition under unlabeled sample scenarios
Maoyou Ye, Xiaoan Yan, Dong Jiang, et al.
Applied Soft Computing (2025), pp. 113053-113053
Closed Access
A hybrid fault diagnosis method for rolling bearings based on GGRU-1DCNN with AdaBN algorithm under multiple load conditions
Lirong Sun, Xiaomin Zhu, Jiannan Xiao, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 7, pp. 076201-076201
Closed Access | Times Cited: 4
Unknown-class recognition adversarial network for open set domain adaptation fault diagnosis of rotating machinery
Ke Wu, Wei Xu, Qiming Shu, et al.
Journal of Intelligent Manufacturing (2024)
Closed Access | Times Cited: 3
Coupled vibration–acoustic emission model for high-speed train bearings with local defects
Cuiping Wang, Hongyuan Qi, Dongming Hou, et al.
Applied Acoustics (2024) Vol. 224, pp. 110142-110142
Closed Access | Times Cited: 2
A multi-source unsupervised fault diagnosis network with residual enhancement attention module for rotating machinery cross-operating conditions
Hangbo Duan, Zongyan Cai, Qingtao Liu, et al.
Journal of Vibration and Control (2024)
Closed Access | Times Cited: 1
TSMDA: intelligent fault diagnosis of rolling bearing with two stage multi-source domain adaptation
Qianqian Zhang, Zhongwei Lv, Caiyun Hao, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 11, pp. 116112-116112
Closed Access
A method for signal components identification in acoustic signal with non-Gaussian background noise using clustering of data in time-frequency domain
Anita Drewnicka, Anna Michalak, Radosław Zimroz, et al.
Applied Acoustics (2024) Vol. 230, pp. 110423-110423
Closed Access
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