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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:

A Systematic Review of Fuzzy Formalisms for Bearing Fault Diagnosis
Chuan Li, José Valente de Oliveira, Mariela Cerrada, et al.
IEEE Transactions on Fuzzy Systems (2018) Vol. 27, Iss. 7, pp. 1362-1382
Closed Access | Times Cited: 118

Showing 1-25 of 118 citing articles:

Deep learning algorithms for rotating machinery intelligent diagnosis: An open source benchmark study
Zhibin Zhao, Tianfu Li, Jingyao Wu, et al.
ISA Transactions (2020) Vol. 107, pp. 224-255
Open Access | Times Cited: 426
A systematic review of deep transfer learning for machinery fault diagnosis
Chuan Li, Shaohui Zhang, Qin Yi, et al.
Neurocomputing (2020) Vol. 407, pp. 121-135
Closed Access | Times Cited: 348
An enhanced convolutional neural network for bearing fault diagnosis based on time–frequency image
Ying Zhang, Kangshuo Xing, Ruxue Bai, et al.
Measurement (2020) Vol. 157, pp. 107667-107667
Closed Access | Times Cited: 222
Research on Remaining Useful Life Prediction of Rolling Element Bearings Based on Time-Varying Kalman Filter
Lingli Cui, Xin Wang, Huaqing Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2019) Vol. 69, Iss. 6, pp. 2858-2867
Closed Access | Times Cited: 186
Deep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016
Xiaohan Chen, Rui Yang, Yihao Xue, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-21
Open Access | Times Cited: 185
Deep Decoupling Convolutional Neural Network for Intelligent Compound Fault Diagnosis
Ruyi Huang, Yixiao Liao, Shaohui Zhang, et al.
IEEE Access (2018) Vol. 7, pp. 1848-1858
Open Access | Times Cited: 179
A Deep Learning Method for Bearing Fault Diagnosis Based on Time-Frequency Image
Jianyu Wang, Zhenling Mo, Heng Zhang, et al.
IEEE Access (2019) Vol. 7, pp. 42373-42383
Open Access | Times Cited: 179
Evolving Deep Echo State Networks for Intelligent Fault Diagnosis
Jianyu Long, Shaohui Zhang, Chuan Li
IEEE Transactions on Industrial Informatics (2019) Vol. 16, Iss. 7, pp. 4928-4937
Closed Access | Times Cited: 170
A novel fault diagnosis method based on CNN and LSTM and its application in fault diagnosis for complex systems
Ting Huang, Qiang Zhang, Xiaoan Tang, et al.
Artificial Intelligence Review (2021) Vol. 55, Iss. 2, pp. 1289-1315
Closed Access | Times Cited: 164
A Scalo Gram-Based CNN Ensemble Method With Density-Aware SMOTE Oversampling for Improving Bearing Fault Diagnosis
Muhammad Irfan, Zohaib Mushtaq, Nabeel Ahmed Khan, et al.
IEEE Access (2023) Vol. 11, pp. 127783-127799
Open Access | Times Cited: 51
Critical Wind Turbine Components Prognostics: A Comprehensive Review
Milad Rezamand, Mojtaba Kordestani, Rupp Carriveau, et al.
IEEE Transactions on Instrumentation and Measurement (2020) Vol. 69, Iss. 12, pp. 9306-9328
Closed Access | Times Cited: 131
Attitude data-based deep hybrid learning architecture for intelligent fault diagnosis of multi-joint industrial robots
Jianyu Long, Jindong Mou, Liangwei Zhang, et al.
Journal of Manufacturing Systems (2020) Vol. 61, pp. 736-745
Closed Access | Times Cited: 120
Condition Monitoring and Fault Diagnosis of Induction Motor
Swapnil Gundewar, Prasad V. Kane
Journal of Vibration Engineering & Technologies (2020) Vol. 9, Iss. 4, pp. 643-674
Closed Access | Times Cited: 120
Bayesian approach and time series dimensionality reduction to LSTM-based model-building for fault diagnosis of a reciprocating compressor
Diego Cabrera, Adriana Guamán, Shaohui Zhang, et al.
Neurocomputing (2019) Vol. 380, pp. 51-66
Closed Access | Times Cited: 111
Rolling bearing fault diagnosis based on multi-channel convolution neural network and multi-scale clipping fusion data augmentation
Ruxue Bai, Quansheng Xu, Zong Meng, et al.
Measurement (2021) Vol. 184, pp. 109885-109885
Closed Access | Times Cited: 97
A Novel Weighted Sparse Representation Classification Strategy Based on Dictionary Learning for Rotating Machinery
Huaqing Wang, Bangyue Ren, Liuyang Song, et al.
IEEE Transactions on Instrumentation and Measurement (2019) Vol. 69, Iss. 3, pp. 712-720
Closed Access | Times Cited: 81
An optimized adaptive PReLU-DBN for rolling element bearing fault diagnosis
Guangxing Niu, Xuan Wang, Michael Golda, et al.
Neurocomputing (2021) Vol. 445, pp. 26-34
Closed Access | Times Cited: 81
A fault dynamic model of high-speed angular contact ball bearings
Yi Qin, Chengcheng Li, Folin Cao, et al.
Mechanism and Machine Theory (2019) Vol. 143, pp. 103627-103627
Closed Access | Times Cited: 75
Wiener-based remaining useful life prediction of rolling bearings using improved Kalman filtering and adaptive modification
Yuxiong Li, Xianzhen Huang, Pengfei Ding, et al.
Measurement (2021) Vol. 182, pp. 109706-109706
Closed Access | Times Cited: 69
Interpretability of deep convolutional neural networks on rolling bearing fault diagnosis
Huixin Yang, Xiang Li, Zhang We
Measurement Science and Technology (2021) Vol. 33, Iss. 5, pp. 055005-055005
Closed Access | Times Cited: 57
Bearing fault diagnosis using time segmented Fourier synchrosqueezed transform images and convolution neural network
Swapnil Gundewar, Prasad V. Kane
Measurement (2022) Vol. 203, pp. 111855-111855
Closed Access | Times Cited: 38
A wiener-based remaining useful life prediction method with multiple degradation patterns
Yuxiong Li, Xianzhen Huang, Tianhong Gao, et al.
Advanced Engineering Informatics (2023) Vol. 57, pp. 102066-102066
Closed Access | Times Cited: 24
A comparison of fuzzy clustering algorithms for bearing fault diagnosis
Chuan Li, Mariela Cerrada, Diego Cabrera, et al.
Journal of Intelligent & Fuzzy Systems (2018) Vol. 34, Iss. 6, pp. 3565-3580
Closed Access | Times Cited: 82
Generative Adversarial Networks Selection Approach for Extremely Imbalanced Fault Diagnosis of Reciprocating Machinery
Diego Cabrera, Fernando Sancho, Jianyu Long, et al.
IEEE Access (2019) Vol. 7, pp. 70643-70653
Open Access | Times Cited: 69
Fault Severity Classification and Size Estimation for Ball Bearings Based on Vibration Mechanism
Lingli Cui, Zhi Jin, Jinfeng Huang, et al.
IEEE Access (2019) Vol. 7, pp. 56107-56116
Open Access | Times Cited: 58
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