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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 Feature Extraction and Fault Diagnosis Method Based on Feature Fusion
Huibin Zhu, Zhangming He, Juhui Wei, et al.
Sensors (2021) Vol. 21, Iss. 7, pp. 2524-2524
Open Access | Times Cited: 68

Showing 1-25 of 68 citing articles:

Unsupervised cross-domain rolling bearing fault diagnosis based on time-frequency information fusion
Hongfeng Tao, Jier Qiu, Yiyang Chen, et al.
Journal of the Franklin Institute (2022) Vol. 360, Iss. 2, pp. 1454-1477
Closed Access | Times Cited: 158
A recursive sparse representation strategy for bearing fault diagnosis
Changkun Han, Wei Lü, Pengxin Wang, et al.
Measurement (2021) Vol. 187, pp. 110360-110360
Closed Access | Times Cited: 55
A Survey on Fault Diagnosis Approaches for Rolling Bearings of Railway Vehicles
Guangxi Yan, Chen Jiang, Yu Bai, et al.
Processes (2022) Vol. 10, Iss. 4, pp. 724-724
Open Access | Times Cited: 44
Rolling mill bearings fault diagnosis based on improved multivariate variational mode decomposition and multivariate composite multiscale weighted permutation entropy
Chen Zhao, Jianliang Sun, Shuilin Lin, et al.
Measurement (2022) Vol. 195, pp. 111190-111190
Closed Access | Times Cited: 41
Prognostics and Health Management of Rotating Machinery of Industrial Robot with Deep Learning Applications—A Review
Prashant Kumar, Salman Khalid, Heung Soo Kim
Mathematics (2023) Vol. 11, Iss. 13, pp. 3008-3008
Open Access | Times Cited: 24
Bearing Fault Diagnosis Based on VMD and Improved CNN
Zhenzhen Jin, Chen Diao, Deqiang He, et al.
Journal of Failure Analysis and Prevention (2022) Vol. 23, Iss. 1, pp. 165-175
Closed Access | Times Cited: 36
Pipeline signal feature extraction method based on multi-feature entropy fusion and local linear embedding
Dandi Yang, Jingyi Lu, Hongli Dong, et al.
Systems Science & Control Engineering (2022) Vol. 10, Iss. 1, pp. 407-416
Open Access | Times Cited: 28
Application of Time-Frequency Analysis in Rotating Machinery Fault Diagnosis
Yihao Bai, Weidong Cheng, Weigang Wen, et al.
Shock and Vibration (2023) Vol. 2023, pp. 1-16
Open Access | Times Cited: 17
Deep Learning-Enhanced Small-Sample Bearing Fault Analysis Using Q-Transform and HOG Image Features in a GRU-XAI Framework
Vipul Dave, Himanshu Borade, Hitesh Agrawal, et al.
Machines (2024) Vol. 12, Iss. 6, pp. 373-373
Open Access | Times Cited: 6
Sparse and low-rank decomposition of the time–frequency representation for bearing fault diagnosis under variable speed conditions
Ran Wang, Haitao Fang, Longjing Yu, et al.
ISA Transactions (2021) Vol. 128, pp. 579-598
Closed Access | Times Cited: 37
Hydraulic directional valve fault diagnosis using a weighted adaptive fusion of multi-dimensional features of a multi-sensor
Jinchuan Shi, Yan Ren, Hesheng Tang, et al.
Journal of Zhejiang University. Science A (2022) Vol. 23, Iss. 4, pp. 257-271
Closed Access | Times Cited: 24
Denoising graph neural network based hydraulic component fault diagnosis method
Zhiwei Qiu, Wanli Li, Tang Tang, et al.
Mechanical Systems and Signal Processing (2023) Vol. 204, pp. 110828-110828
Closed Access | Times Cited: 14
Neural Network and L-kurtosis for Diagnosing Rolling Element Bearing Faults
Meriem Behim, Merabet Leila, Salah Saad
Journal of Electrical Engineering and Technology (2024) Vol. 19, Iss. 4, pp. 2597-2606
Closed Access | Times Cited: 4
Fault diagnosis of motor bearing in complex scenarios based on Mamba and Indicative Contrastive Learning
Xu Jun, Yunji Zhao, Wenming Bao, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 146, pp. 110216-110216
Closed Access
Scalable bearing fault diagnosis using metaheuristic feature selection and machine learning for diverse operating conditions
B. R. Nayana, R. Subha, Rekha Radhakrishnan, et al.
Systems Science & Control Engineering (2025) Vol. 13, Iss. 1
Open Access
Intelligent bearing faults diagnosis in non-stationary conditions based on angular resampling and support vector machine
Fatma Bouali, Semchedine Fedala, Hugo André, et al.
Comptes Rendus Mécanique (2025) Vol. 353, Iss. G1, pp. 499-518
Open Access
Multi-type feature extraction and classification of leakage in oil pipeline network using digital twin technology
E. B. Priyanka, S. Thangavel
Journal of Ambient Intelligence and Humanized Computing (2022) Vol. 13, Iss. 12, pp. 5885-5901
Closed Access | Times Cited: 16
Hybrid Multimodal Feature Fusion with Multi-Sensor for Bearing Fault Diagnosis
Zhenzhong Xu, Xu Chen, Yilin Li, et al.
Sensors (2024) Vol. 24, Iss. 6, pp. 1792-1792
Open Access | Times Cited: 3
A small sample bearing fault diagnosis method based on novel Zernike moment feature attention convolutional neural network
Yunji Zhao, Xu Jun
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 066208-066208
Closed Access | Times Cited: 3
Rolling Bearing Remaining Useful Life Prediction Based on CNN-VAE-MBiLSTM
Lei Yang, Yibo Jiang, Kang Zeng, et al.
Sensors (2024) Vol. 24, Iss. 10, pp. 2992-2992
Open Access | Times Cited: 3
Research on SVM-Based Bearing Fault Diagnosis Modeling and Multiple Swarm Genetic Algorithm Parameter Identification Method
Changchun Mo, Huizi Han, Mei Liu, et al.
Mathematics (2023) Vol. 11, Iss. 13, pp. 2864-2864
Open Access | Times Cited: 8
A Study of Noise Effect in Electrical Machines Bearing Fault Detection and Diagnosis Considering Different Representative Feature Models
Dimitrios A. Moysidis, Georgios D. Karatzinis, Yiannis S. Boutalis, et al.
Machines (2023) Vol. 11, Iss. 11, pp. 1029-1029
Open Access | Times Cited: 8
A Comparative Study on Recent Automatic Data Fusion Methods
Luis Manuel Pereira, Addisson Salazar, Luis Vergara
Computers (2023) Vol. 13, Iss. 1, pp. 13-13
Open Access | Times Cited: 8
Richly connected spatial–temporal graph neural network for rotating machinery fault diagnosis with multi-sensor information fusion
Chengming Wang, Yanxue Wang, Yiyan Wang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 225, pp. 112230-112230
Closed Access | Times Cited: 2
Fault Diagnosis Method for Rolling Mill Multi Row Bearings Based on AMVMD-MC1DCNN under Unbalanced Dataset
Chen Zhao, Jianliang Sun, Shuilin Lin, et al.
Sensors (2021) Vol. 21, Iss. 16, pp. 5494-5494
Open Access | Times Cited: 17
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