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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:

An efficient approach based on a novel 1D-LBP for the detection of bearing failures with a hybrid deep learning method
Yılmaz Kaya, Melih Kuncan, Eyyüp Akcan, et al.
Applied Soft Computing (2024) Vol. 155, pp. 111438-111438
Closed Access | Times Cited: 14

Showing 14 citing articles:

Insights into modern machine learning approaches for bearing fault classification: A systematic literature review
Afzal Ahmed Soomro, Masdi Muhammad, Ainul Akmar Mokhtar, et al.
Results in Engineering (2024) Vol. 23, pp. 102700-102700
Open Access | Times Cited: 19
Fault diagnosis of rotating machinery with high-dimensional imbalance samples based on wavelet random forest
Zhen Guo, Wenliao Du, Chuan Li, et al.
Measurement (2025), pp. 116936-116936
Closed Access | Times Cited: 2
An ensemble deep learning network based on 2D convolutional neural network and 1D LSTM with self-attention for bearing fault diagnosis
Liying Wang, Weiguo Zhao
Applied Soft Computing (2025), pp. 112889-112889
Closed Access | Times Cited: 1
Enhanced fault diagnosis of rolling bearings using an improved inception-lstm network
Lunpan Wei, Xiuyan Peng, Yunpeng Cao
Nondestructive Testing And Evaluation (2024), pp. 1-20
Closed Access | Times Cited: 8
A novel convolutional neural network with global perception for bearing fault diagnosis
Xianguo Li, Ying Chen, Yi Liu
Engineering Applications of Artificial Intelligence (2025) Vol. 143, pp. 109986-109986
Closed Access
A multi-source domain adaption intelligent fault diagnosis method based on asymmetric adversarial training
Dan Yang, Tianyu Ma, Zhipeng Li
Measurement Science and Technology (2025) Vol. 36, Iss. 3, pp. 036123-036123
Closed Access
Application of a multi-dimensional synchronous feature mode decomposition for machinery fault diagnosis
Huifang Shi, Yonghao Miao, Xun Wang, et al.
ISA Transactions (2025)
Closed Access
Identification of compound faults of rolling bearing based on envelope-cross-correlation and improved 1D-LBP
Xin Wang, Mingyue Yu, Yunbo Wang, et al.
Measurement Science and Technology (2025) Vol. 36, Iss. 4, pp. 046120-046120
Closed Access
A novel shift-invariant dictionary learning approach integrated with a hidden Markov model for diagnosing bearing faults in time-varying conditions
Z. Fan, Jiquan Shen, Yang Shaobin, et al.
Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering (2025)
Closed Access
A novel digital twin-enabled three-stage feature imputation framework for non-contact intelligent fault diagnosis
Yue Yu, Hamid Reza Karimi, Len Gelman, et al.
Advanced Engineering Informatics (2025) Vol. 66, pp. 103434-103434
Open Access
Cost effective detection of uneven mounting fault in rotary wing drone motors with a CNN based method
Nurdoğan Ceylan, Eyüp Sönmez, Sezgin Kaçar
Signal Image and Video Processing (2024) Vol. 18, Iss. 11, pp. 8049-8059
Closed Access | Times Cited: 2
Enhancing induction machine fault detection through machine learning: Time and frequency analysis of vibration signals
A. Daas, Bilal Sari, Jiajia Jia, et al.
Measurement (2024), pp. 116023-116023
Closed Access | Times Cited: 2
Intelligent diagnosis method of torque-angle dynamometer cards for beam pumping units based on transfer learning
Jincheng Huang, Wenjun Huang, Zi‐Ming Feng, et al.
Geoenergy Science and Engineering (2024) Vol. 241, pp. 213138-213138
Closed Access
Investigating Bearing and Gear Vibrations with a Micro-electro-mechanical Systems (MEMS) and Machine Learning Approach
Gagandeep Sharma, Tejbir Kaur, Sanjay Kumar Mangal, et al.
Results in Engineering (2024), pp. 103499-103499
Open Access
An enhanced deep intelligent model with feature fusion and ensemble learning for the fault diagnosis of rotating machinery
Kejia Zhuang, Bin Deng, Huai Chen, et al.
Structural Health Monitoring (2024)
Closed Access
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