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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:

Lite and Efficient Deep Learning Model for Bearing Fault Diagnosis Using the CWRU Dataset
Soo-Bin Yoo, Jung-Hwa Jo, Sang-Woo Ban
Sensors (2023) Vol. 23, Iss. 6, pp. 3157-3157
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Improving Bearing Fault Identification by Using Novel Hybrid Involution-Convolution Feature Extraction With Adversarial Noise Injection in Conditional GANs
Muhammad Irfan, Zohaib Mushtaq, Nabeel Ahmed Khan, et al.
IEEE Access (2023) Vol. 11, pp. 118253-118267
Open Access | Times Cited: 50
Machine Fault Detection Using a Hybrid CNN-LSTM Attention-Based Model
Andressa Borré, Laio Oriel Seman, Eduardo Camponogara, et al.
Sensors (2023) Vol. 23, Iss. 9, pp. 4512-4512
Open Access | Times Cited: 49
Bearing Fault Diagnosis With Envelope Analysis and Machine Learning Approaches Using CWRU Dataset
M. Alonso-González, Vicente García‐Díaz, Benjamín López Pérez, et al.
IEEE Access (2023) Vol. 11, pp. 57796-57805
Open Access | Times Cited: 34
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: 12
An Interpretable Parallel Spatial CNN-LSTM Architecture for Fault Diagnosis in Rotating Machinery
Qianyu Zhou, Jiong Tang
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 19, pp. 31730-31744
Closed Access | Times Cited: 5
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
Ternary Precursor Centrifuge Rolling Bearing Fault Diagnosis Based on Adaptive Sample Length Adjustment of 1DCNN-SeNet
Feng Xu, Zhen Sui, Jiangang Ye, et al.
Processes (2024) Vol. 12, Iss. 4, pp. 702-702
Open Access | Times Cited: 4
Investigating the Effect of Vibration Signal Length on Bearing Fault Classification Using Wavelet Scattering Transform
Suparerk Janjarasjitt
Sensors (2025) Vol. 25, Iss. 3, pp. 699-699
Open Access
Multi‐Channel Deep Pulse‐Coupled Net: A Novel Bearing Fault Diagnosis Framework
Yanxi Wu, Yalin Yang, Zhuoran Yang, et al.
IET Image Processing (2025) Vol. 19, Iss. 1
Open Access
Exploration of deep learning-driven multimodal information fusion frameworks and their application in lower limb motion recognition
Changhe Zhang, Zidong Yu, Xiaoyun Wang, et al.
Biomedical Signal Processing and Control (2024) Vol. 96, pp. 106551-106551
Closed Access | Times Cited: 3
Multi-resolution short-time Fourier transform providing deep features for 3D CNN to classify rolling bearing fault vibration signals
Meng Zhang
Engineering Research Express (2024) Vol. 6, Iss. 3, pp. 035201-035201
Open Access | Times Cited: 3
Anomaly Detection Methods for Industrial Applications: A Comparative Study
Maria Antonietta Panza, Marco Pota, Massimo Esposito
Electronics (2023) Vol. 12, Iss. 18, pp. 3971-3971
Open Access | Times Cited: 8
Interpretable Dual-branch EMGNet: A transfer learning-based network for inter-subject lower limb motion intention recognition
Changhe Zhang, Xiaoyun Wang, Zidong Yu, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 130, pp. 107761-107761
Closed Access | Times Cited: 8
A Novel Deep Convolutional Neural Network Combining Global Feature Extraction and Detailed Feature Extraction for Bearing Compound Fault Diagnosis
Shuzhen Han, Pingjuan Niu, Shijie Luo, et al.
Sensors (2023) Vol. 23, Iss. 19, pp. 8060-8060
Open Access | Times Cited: 3
Fault Diagnosis Method of Roadheader Bearing Based on VMD and Domain Adaptive Transfer Learning
Xiaofei Qu, Yongkang Zhang
Sensors (2023) Vol. 23, Iss. 11, pp. 5134-5134
Open Access | Times Cited: 2
Remaining Useful Life Prediction of Ball Bearings Using Deep Learning Techniques
Ayush Narang, Kashika Singh, Harshita Gaur, et al.
(2024), pp. 908-913
Closed Access
Decoding of lower limb continuous movement intention from multi-channel sEMG and design of adaptive exoskeleton controller
Xiaoyun Wang, Changhe Zhang, Zidong Yu, et al.
Biomedical Signal Processing and Control (2024) Vol. 94, pp. 106245-106245
Closed Access
Bearing Fault Diagnosis Based on Prominence Peak-Picking IMFs Selection and PSO-SSAE
Mohd Syahril Ramadhan Mohd Saufi, M. Salman Leong, Lim Meng Hee, et al.
Lecture notes in networks and systems (2024), pp. 181-197
Closed Access
Kernel Extreme Learning Machine bearing fault diagnosis based on empirical wavelet transform feature extraction and Sparrow search algorithm optimization
Maidina Bahati, Maimaitireyimu Abulizi
(2024), pp. 1521-1525
Closed Access
Rulman Titreşim Verilerinden Derin Öğrenme Tabanlı Arıza Tespiti
Engin Oğuzay, Murat Balta
Karadeniz Fen Bilimleri Dergisi (2024) Vol. 14, Iss. 3, pp. 1159-1175
Open Access
Graph-Based Feature Engineering for Enhanced Machine Learning in Rolling Element Bearing Fault Diagnosis
Seyed Mohammad Hosseini, Abolfazl Dibaji, Sadegh Sulaimany
Engineering Research Express (2024) Vol. 6, Iss. 4, pp. 045234-045234
Closed Access
A computationally efficient method for induction motor bearing fault detection based on parallel convolutions and semi-supervised GAN
Muhammad Irfan, Nabeel Ahmed Khan, Zohaib Mushtaq, et al.
Nondestructive Testing And Evaluation (2024), pp. 1-27
Closed Access
Prototype space boundary alignment network for bearing continuous fault diagnosis under class-incremental scenarios
Zhenzhong He, Juanjuan Shi, Weiguo Huang, et al.
IEEE Sensors Journal (2024) Vol. 25, Iss. 1, pp. 1076-1085
Closed Access
GRUDMU-DSCNN: An edge computing method for fault diagnosis with missing data
Ziyang Yu, Yanzhi Wang, Xiaofeng Zong, et al.
Applied Intelligence (2024) Vol. 55, Iss. 2
Closed Access
Systematic Review of Bearing Component Failure: Strategies for Diagnosis and Prognosis in Rotating Machinery
Komandur S. Sunder Raj, Shahil Kumar, Rahul Kumar
Arabian Journal for Science and Engineering (2024)
Closed Access
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