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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.

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Showing 11 citing articles:

Investigation of the Contact Characteristics of a Single-Nut Ball Screw Considering Geometric Errors
Jun Liu, Hua-Xi Zhou, Xiao-Yi Wang, et al.
Lubricants (2025) Vol. 13, Iss. 2, pp. 57-57
Open Access
A review of artificial intelligence application for machining surface quality prediction: from key factors to model development
Jeong Hoon Ko, Chen Yin
Journal of Intelligent Manufacturing (2025)
Open Access
Cross-domain adaptation network based on attention mechanism for tool wear prediction
Jianliang He, Yuxin Sun, Chen Yin, et al.
Journal of Intelligent Manufacturing (2022) Vol. 34, Iss. 8, pp. 3365-3387
Closed Access | Times Cited: 22
Hilbert spectrum analysis method of blast vibration signal based on HHT instantaneous phase optimization
Erhu Dong, Long An, Yuanhui Li, et al.
Applied Acoustics (2022) Vol. 192, pp. 108732-108732
Closed Access | Times Cited: 16
Leveraging artificial intelligence for real-time indirect tool condition monitoring: From theoretical and technological progress to industrial applications
Delin Liu, Zhanqiang Liu, Bing Wang, et al.
International Journal of Machine Tools and Manufacture (2024) Vol. 202, pp. 104209-104209
Closed Access | Times Cited: 3
Research Progress of Noise in High-Speed Cutting Machining
Weihua Wei, Yunyue Shang, You Peng, et al.
Sensors (2022) Vol. 22, Iss. 10, pp. 3851-3851
Open Access | Times Cited: 13
Attention-driven transfer learning framework for dynamic model guided time domain chatter detection
Chen Yin, Yulin Wang, Jeong Hoon Ko, et al.
Journal of Intelligent Manufacturing (2023) Vol. 35, Iss. 4, pp. 1867-1885
Closed Access | Times Cited: 7
A multi-sensor monitoring methodology for grinding wheel wear evaluation based on INFO-SVM
Linlin Wan, Zejun Chen, Xianyang Zhang, et al.
Mechanical Systems and Signal Processing (2023) Vol. 208, pp. 111003-111003
Closed Access | Times Cited: 7
Remaining useful lifetime estimation for metal-bonded grinding tools using hybrid machine learning
Emil Sauter, Hanyu Sun, Marius Winter, et al.
The International Journal of Advanced Manufacturing Technology (2022) Vol. 123, Iss. 9-10, pp. 3243-3260
Closed Access | Times Cited: 3
Thermal behaviors in the metal high-efficiency grinding process under simulated vacuum conditions: state of the art and future perspectives
Zhongyu Zhang, Jinsheng Zhang, Jingkun Wang, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 133, Iss. 9-10, pp. 4133-4170
Closed Access
Resolving mode mixing in wheel–rail surface defect detection using EMD based on binary time scale
Jiang Hua, WU Zhi-quan
Measurement Science and Technology (2023) Vol. 35, Iss. 3, pp. 035015-035015
Closed Access | Times Cited: 1
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