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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 diagnosis based on optimal convolution neural network
Yongjian Sun, Shaohui Li
Measurement (2022) Vol. 190, pp. 110702-110702
Closed Access | Times Cited: 57

Showing 26-50 of 57 citing articles:

Vibration Signal Analysis for Intelligent Rotating Machinery Diagnosis and Prognosis: A Comprehensive Systematic Literature Review
Ikram Bagri, Karim Tahiry, Aziz Hraiba, et al.
Vibration (2024) Vol. 7, Iss. 4, pp. 1013-1062
Open Access | Times Cited: 1
Domain adaptive networks with limited data for rotating machinery fault diagnosis: a case of study of gears
Xueyi Li, Tianyu Yu, Qiushi He, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 12, pp. 125123-125123
Closed Access | Times Cited: 4
Fault Diagnosis Method for Bearing Based on Digital Twin
Xuyang Xie, Zichun Yang, Wenhao Wu, et al.
Mathematical Problems in Engineering (2022) Vol. 2022, pp. 1-15
Open Access | Times Cited: 7
Fault Diagnosis of Rolling Bearings Based on the Improved Symmetrized Dot Pattern Enhanced Convolutional Neural Networks
Xiaoping Liu, Lijian Xia, Jian Shi, et al.
Journal of Vibration Engineering & Technologies (2023) Vol. 12, Iss. 2, pp. 1897-1908
Closed Access | Times Cited: 3
Application of Multi-Scale Convolutional Neural Networks and Extreme Learning Machines in Mechanical Fault Diagnosis
Wei Zhang, Junxia Li, Shuai Huang, et al.
Machines (2023) Vol. 11, Iss. 5, pp. 515-515
Open Access | Times Cited: 3
Sound Based Fault Diagnosis Method Based on Variational Mode Decomposition and Support Vector Machine
Xiaojing Yin, Qiangqiang He, Hao Zhang, et al.
Electronics (2022) Vol. 11, Iss. 15, pp. 2422-2422
Open Access | Times Cited: 4
Improved dynamic state estimation of power system using unscented Kalman filter with more accurate prediction model
Yanjie Yu, Qiang Li, Chuchu Chen, et al.
Energy Reports (2022) Vol. 8, pp. 364-376
Open Access | Times Cited: 4
A Hybrid Data-Driven Soft Sensor Framework for Torque Estimation
Le Wang, Xueke Zheng, Ying Wang, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 20, pp. 24993-25004
Closed Access | Times Cited: 2
IRMSwin-T: A lightweight shifted windows transformer based on inverted residual structure and residual multi-layer perceptron for rolling bearing fault diagnosis
Shanshan Ding, Renwen Chen, Hao Liu, et al.
Review of Scientific Instruments (2023) Vol. 94, Iss. 9
Closed Access | Times Cited: 2
MITDCNN: A multi-modal input Transformer-based deep convolutional neural network for misfire signal detection in high-noise diesel engines
Wenjie Li, Xiangpeng Liu, D.H. Wang, et al.
Expert Systems with Applications (2023) Vol. 238, pp. 121797-121797
Closed Access | Times Cited: 2
On fault diagnosis using image-based deep learning networks based on vibration signals
Zhenxing Ren, Jianfeng Guo
Multimedia Tools and Applications (2023) Vol. 83, Iss. 15, pp. 44555-44580
Closed Access | Times Cited: 2
Research on bearing fault diagnosis technology based on machine learning
Xia Yu, Xiaojun Guo, ErChuan Su, et al.
International Journal of Industrial Optimization (2024), pp. 45-59
Open Access
Bayesian estimation of output combining method for bridge damage identification using multiple CNNs
Ryota Yamada, Atsushi Iwasaki, Yoshihide ENDO, et al.
Transactions of the JSME (in Japanese) (2024) Vol. 90, Iss. 934, pp. 24-00037
Open Access
Bearing fault detection using a method involving absolute value spectrum and impulsivity evaluation
Karim Bouaouiche, Yamina Menasria, Dalila Khalfa
Diagnostyka (2024) Vol. 25, Iss. 2, pp. 1-9
Open Access
MARNet: Multi-head attention residual network for rolling bearing fault diagnosis under noisy condition
Linfeng Deng, Guojun Wang, Cheng Zhao, et al.
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science (2024) Vol. 238, Iss. 19, pp. 9726-9747
Closed Access
Intelligent Fault Diagnosis of Bearings Using a Flexible Residual Neural Network Tuned by Seagull Optimization Algorithm
Xianfeng Li, Chuang Chen, Jiantao Shi
2022 IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS) (2024), pp. 286-290
Closed Access
Knowledge Push Mechanism of Rolling Bearing Fault Diagnosis Employing Deep Residual Network Architecture
Abdullah-Al Muin, Shahrukh Khan, Md Helal Miah
SAE technical papers on CD-ROM/SAE technical paper series (2024) Vol. 1
Closed Access
A fully automatic bearing fault diagnosis method based on an improved polar coordinate image texture
Li Bi, Li Zhi, Deqiang He
Mechanical Systems and Signal Processing (2024) Vol. 224, pp. 112036-112036
Closed Access
Metrological parameter planning method based on a multi-head sparse graph attention network for airborne products
Shengjie Kong, Xiang Huang, Shuanggao Li, et al.
Measurement (2024) Vol. 242, pp. 116149-116149
Closed Access
Dilated dynamic supervised contrastive learning framework for fault diagnosis under imbalanced dataset conditions
Rui Yang, Jia Shi, Houliang Wang, et al.
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science (2024)
Closed Access
A lightweight and precision dual track 1D and 2D feature fusion convolutional network for machinery equipment fault diagnosis
Chaoquan Mo, Ke Huang, Houxin Ji
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Rolling bearing fault diagnosis method based on gramian angular difference field and dynamic self-calibrated convolution module
Chunli Liu, Jiarui Bai, Linlin Xue, et al.
PLoS ONE (2024) Vol. 19, Iss. 12, pp. e0314898-e0314898
Open Access
Fault Diagnosis of Rolling Bearing Based on Variational Mode Decomposition and Improved Canberra Distance in Symmetrized Dot Pattern Image
Wei Wang, Jian Wang, Yongjian Sun
Journal of Artificial Intelligence Machine Learning and Data Science (2023) Vol. 1, Iss. 1, pp. 39-48
Open Access | Times Cited: 1
Fault diagnosis method of rolling bearing based on SE-DRN
Liying Jiang, Tianci Wang, Jianguo Cui, et al.
2022 34th Chinese Control and Decision Conference (CCDC) (2023), pp. 608-614
Closed Access | Times Cited: 1
Research on the Rapid Diagnostic Method of Rolling Bearing Fault Based on Cloud–Edge Collaboration
Xianghong Tang, Lei Xu, Gongsheng Chen
Entropy (2022) Vol. 24, Iss. 9, pp. 1277-1277
Open Access | Times Cited: 2

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