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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:

Bearing Fault Classification Using Ensemble Empirical Mode Decomposition and Convolutional Neural Network
Rafia Nishat Toma, Cheol Hong Kim, Jong-Myon Kim
Electronics (2021) Vol. 10, Iss. 11, pp. 1248-1248
Open Access | Times Cited: 53

Showing 1-25 of 53 citing articles:

Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach : A review of two decades of research
Shreyas Gawde, Shruti Patil, Satish Kumar, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106139-106139
Open Access | Times Cited: 130
A nearly end-to-end deep learning approach to fault diagnosis of wind turbine gearboxes under nonstationary conditions
Liangwei Zhang, Qi Fan, Jing Lin, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 119, pp. 105735-105735
Closed Access | Times Cited: 66
SHapley Additive exPlanations (SHAP) for Efficient Feature Selection in Rolling Bearing Fault Diagnosis
Mailson Ribeiro Santos, Luiz Affonso Guedes, Ignacio Sánchez-Gendriz
Machine Learning and Knowledge Extraction (2024) Vol. 6, Iss. 1, pp. 316-341
Open Access | Times Cited: 13
Bearing fault diagnosis using multiple feature selection algorithms with SVM
Rajeev Kumar, R. S. Anand
Progress in Artificial Intelligence (2024) Vol. 13, Iss. 2, pp. 119-133
Closed Access | Times Cited: 9
Rolling Surface Defect Inspection for Drum-Shaped Rollers Based on Deep Learning
Jiamin Tao, Yongjian Zhu, Frank Jiang, et al.
IEEE Sensors Journal (2022) Vol. 22, Iss. 9, pp. 8693-8700
Closed Access | Times Cited: 36
An Edge Intelligent Method for Bearing Fault Diagnosis Based on a Parameter Transplantation Convolutional Neural Network
Xiang Ding, Hang Wang, Zheng Cao, et al.
Electronics (2023) Vol. 12, Iss. 8, pp. 1816-1816
Open Access | Times Cited: 16
DWT-LSTM-Based Fault Diagnosis of Rolling Bearings with Multi-Sensors
Kai Gu, Yu Zhang, Xiaobo Liu, et al.
Electronics (2021) Vol. 10, Iss. 17, pp. 2076-2076
Open Access | Times Cited: 38
Novel Bearing Fault Diagnosis Using Gaussian Mixture Model-Based Fault Band Selection
Andrei S. Maliuk, Alexander E. Prosvirin, Zahoor Ahmad, et al.
Sensors (2021) Vol. 21, Iss. 19, pp. 6579-6579
Open Access | Times Cited: 35
Hardware implementation of bearing fault diagnosis using empirical mode decomposition
Swapnil Ninawe, R. B. Deshmukh
Nondestructive Testing And Evaluation (2024), pp. 1-18
Closed Access | Times Cited: 4
Heterogeneous vibration data preprocessing method for fault detection
Donatien Claeyssens, Dorsaf Zekri, David M. Thierry, et al.
Procedia Computer Science (2025) Vol. 253, pp. 2127-2136
Open Access
A Deep Autoencoder-Based Convolution Neural Network Framework for Bearing Fault Classification in Induction Motors
Rafia Nishat Toma, Farzin Piltan, Jong-Myon Kim
Sensors (2021) Vol. 21, Iss. 24, pp. 8453-8453
Open Access | Times Cited: 32
A Bearing Fault Classification Framework Based on Image Encoding Techniques and a Convolutional Neural Network under Different Operating Conditions
Rafia Nishat Toma, Farzin Piltan, Kichang Im, et al.
Sensors (2022) Vol. 22, Iss. 13, pp. 4881-4881
Open Access | Times Cited: 20
Diesel Engine Fault Diagnosis Method Based on Optimized VMD and Improved CNN
Xianbiao Zhan, Huajun Bai, Hao Yan, et al.
Processes (2022) Vol. 10, Iss. 11, pp. 2162-2162
Open Access | Times Cited: 20
PHM SURVEY: Implementation of Prognostic Methods for Monitoring Industrial Systems
Abdenour Soualhi, M. Lamraoui, Bilal El Yousfi, et al.
Energies (2022) Vol. 15, Iss. 19, pp. 6909-6909
Open Access | Times Cited: 18
Failure diagnosis of a compressor subjected to surge events: A data-driven framework
Leonardo Leoni, Filippo De Carlo, Mohammad Mahdi Abaei, et al.
Reliability Engineering & System Safety (2023) Vol. 233, pp. 109107-109107
Open Access | Times Cited: 9
Automatic bolt tightness detection using acoustic emission and deep learning
Wei Fu, Ruohua Zhou, Ziye Guo
Structures (2023) Vol. 55, pp. 1774-1782
Open Access | Times Cited: 9
Mayfly optimization algorithm: a review
Mohit N. Bogar, Ishwar D Shirodkar, Omkar Kulkarni, et al.
Journal of Mechatronics and Artificial Intelligence in Engineering (2024) Vol. 5, Iss. 1, pp. 17-30
Open Access | Times Cited: 3
A multi-fault diagnosis method for rolling bearings
Kai Zhang, Eryu Zhu, Yimin Zhang, et al.
Signal Image and Video Processing (2024) Vol. 18, Iss. 11, pp. 8413-8426
Closed Access | Times Cited: 3
A Noise-Robust CNN Architecture with Global Attention and Gated Convolutional Kernels for Bearing Fault Detection
Bowen Xiao, Yongpeng Zhao, Chengjiang Zhou, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 8, pp. 086142-086142
Closed Access | Times Cited: 2
A Wind Turbine Bearing Fault Detection Method Based on Improved CEEMDAN and AR-MEDA
Ilyes Djemili, Ammar Medoued, Youcef Soufı
Journal of Vibration Engineering & Technologies (2023) Vol. 12, Iss. 3, pp. 4225-4246
Closed Access | Times Cited: 6
Intelligent Analysis of Vibration Faults in Hydroelectric Generating Units Based on Empirical Mode Decomposition
Hong Tian, Lijing Yang, Peng Ji
Processes (2023) Vol. 11, Iss. 7, pp. 2040-2040
Open Access | Times Cited: 5
Statistical Analysis of Vibration Signal Frequency During Inner Race Fault of Rolling Ball Bearings
Rajeev Kumar, R. S. Anand
Journal of Failure Analysis and Prevention (2023) Vol. 23, Iss. 5, pp. 2260-2274
Closed Access | Times Cited: 5
A comprehensive review of mechanical fault diagnosis methods based on convolutional neural network
Junjian Hou, Xikang Lu, Yudong Zhong, et al.
Journal of Vibroengineering (2023) Vol. 26, Iss. 1, pp. 44-65
Open Access | Times Cited: 5
Novel Preprocessing of Multimodal Condition Monitoring Data for Classifying Induction Motor Faults Using Deep Learning Methods
Shahd Hejazi, Michael Packianather, Ying Liu
(2022)
Closed Access | Times Cited: 8
A methodological integration of fisher score technique with intelligent machine learning methods for ball bearing fault investigation
Rajeev Kumar, R. S. Anand
Engineering Research Express (2024) Vol. 6, Iss. 2, pp. 025523-025523
Open Access | Times Cited: 1
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