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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:

Intelligent fault diagnosis among different rotating machines using novel stacked transfer auto-encoder optimized by PSO
Haidong Shao, Ziyang Ding, Junsheng Cheng, et al.
ISA Transactions (2020) Vol. 105, pp. 308-319
Closed Access | Times Cited: 98

Showing 1-25 of 98 citing articles:

A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges
Weihua Li, Ruyi Huang, Jipu Li, et al.
Mechanical Systems and Signal Processing (2021) Vol. 167, pp. 108487-108487
Open Access | Times Cited: 520
Unsupervised domain-share CNN for machine fault transfer diagnosis from steady speeds to time-varying speeds
Hongru Cao, Haidong Shao, Xiang Zhong, et al.
Journal of Manufacturing Systems (2021) Vol. 62, pp. 186-198
Closed Access | Times Cited: 206
Intelligent fault diagnosis of hydraulic piston pump based on deep learning and Bayesian optimization
Shengnan Tang, Yong Zhu, Shouqi Yuan
ISA Transactions (2022) Vol. 129, pp. 555-563
Closed Access | Times Cited: 121
Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals
Bayu Adhi Tama, Malinda Vania, Seung‐Chul Lee, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 5, pp. 4667-4709
Open Access | Times Cited: 119
Intelligent fault diagnosis of hydraulic piston pump combining improved LeNet-5 and PSO hyperparameter optimization
Yong Zhu, Guangpeng Li, Rui Wang, et al.
Applied Acoustics (2021) Vol. 183, pp. 108336-108336
Closed Access | Times Cited: 117
Acoustic signal-based fault detection of hydraulic piston pump using a particle swarm optimization enhancement CNN
Yong Zhu, Guangpeng Li, Shengnan Tang, et al.
Applied Acoustics (2022) Vol. 192, pp. 108718-108718
Closed Access | Times Cited: 87
An adaptive deep learning model towards fault diagnosis of hydraulic piston pump using pressure signal
Shengnan Tang, Yong Zhu, Shouqi Yuan
Engineering Failure Analysis (2022) Vol. 138, pp. 106300-106300
Closed Access | Times Cited: 76
Fault diagnosis in rotating machines based on transfer learning: Literature review
Iqbal Misbah, C.K.M. Lee, K. L. Keung
Knowledge-Based Systems (2023) Vol. 283, pp. 111158-111158
Closed Access | Times Cited: 57
An unsupervised domain adaptation approach with enhanced transferability and discriminability for bearing fault diagnosis under few-shot samples
Wengang Ma, Yadong Zhang, Liang Ma, et al.
Expert Systems with Applications (2023) Vol. 225, pp. 120084-120084
Closed Access | Times Cited: 44
Application of deep learning to fault diagnosis of rotating machineries
Hao Su, Ling Xiang, Aijun Hu
Measurement Science and Technology (2024) Vol. 35, Iss. 4, pp. 042003-042003
Open Access | Times Cited: 15
Rolling bearing fault diagnosis using optimal ensemble deep transfer network
Xingqiu Li, Hongkai Jiang, Ruixin Wang, et al.
Knowledge-Based Systems (2020) Vol. 213, pp. 106695-106695
Closed Access | Times Cited: 134
A reinforcement ensemble deep transfer learning network for rolling bearing fault diagnosis with Multi-source domains
Xingqiu Li, Hongkai Jiang, Min Xie, et al.
Advanced Engineering Informatics (2021) Vol. 51, pp. 101480-101480
Closed Access | Times Cited: 98
Multi-class fuzzy support matrix machine for classification in roller bearing fault diagnosis
Haiyang Pan, Haifeng Xu, Jinde Zheng, et al.
Advanced Engineering Informatics (2021) Vol. 51, pp. 101445-101445
Closed Access | Times Cited: 84
Advanced Metaheuristic Techniques for Mechanical Design Problems: Review
Mohamed Abd Elaziz, Ammar H. Elsheikh, Diego Oliva, et al.
Archives of Computational Methods in Engineering (2021) Vol. 29, Iss. 1, pp. 695-716
Closed Access | Times Cited: 81
Extreme learning Machine-based classifier for fault diagnosis of rotating Machinery using a residual network and continuous wavelet transform
Wei Hao, Qinghua Zhang, Minghu Shang, et al.
Measurement (2021) Vol. 183, pp. 109864-109864
Closed Access | Times Cited: 73
An integrated deep multiscale feature fusion network for aeroengine remaining useful life prediction with multisensor data
Xingqiu Li, Hongkai Jiang, Yuan Liu, et al.
Knowledge-Based Systems (2021) Vol. 235, pp. 107652-107652
Closed Access | Times Cited: 73
Intelligent fault diagnosis of planetary gearbox based on adaptive normalized CNN under complex variable working conditions and data imbalance
Chaoge Wang, Hongkun Li, Kongliang Zhang, et al.
Measurement (2021) Vol. 180, pp. 109565-109565
Closed Access | Times Cited: 70
A chatter detection method in milling of thin-walled TC4 alloy workpiece based on auto-encoding and hybrid clustering
Yichao Dun, Lida Zhu, Boling Yan, et al.
Mechanical Systems and Signal Processing (2021) Vol. 158, pp. 107755-107755
Closed Access | Times Cited: 65
Unsupervised domain adaptation of bearing fault diagnosis based on Join Sliced Wasserstein Distance
Pengfei Chen, Rongzhen Zhao, Tianjing He, et al.
ISA Transactions (2022) Vol. 129, pp. 504-519
Closed Access | Times Cited: 65
Cross-domain meta learning fault diagnosis based on multi-scale dilated convolution and adaptive relation module
Ruiyi Ma, Tian Han, Wenxin Lei
Knowledge-Based Systems (2022) Vol. 261, pp. 110175-110175
Closed Access | Times Cited: 45
An improved multi-channel graph convolutional network and its applications for rotating machinery diagnosis
Chaoying Yang, Jie Liu, Kaibo Zhou, et al.
Measurement (2022) Vol. 190, pp. 110720-110720
Closed Access | Times Cited: 43
A deep reinforcement transfer convolutional neural network for rolling bearing fault diagnosis
Zhenghong Wu, Hongkai Jiang, Shaowei Liu, et al.
ISA Transactions (2022) Vol. 129, pp. 505-524
Closed Access | Times Cited: 37
A novel transfer learning network with adaptive input length selection and lightweight structure for bearing fault diagnosis
Guiting Tang, Cai Yi, Lei Liu, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106395-106395
Closed Access | Times Cited: 29
Attention-based Gate Recurrent Unit for remaining useful life prediction in prognostics
Ruiguan Lin, Huawei Wang, Minglan Xiong, et al.
Applied Soft Computing (2023) Vol. 143, pp. 110419-110419
Closed Access | Times Cited: 24
A novel method of rolling bearings fault diagnosis based on singular spectrum decomposition and optimized stochastic configuration network
Shenquan Wang, Ganggang Lian, Chao Cheng, et al.
Neurocomputing (2024) Vol. 574, pp. 127278-127278
Closed Access | Times Cited: 11
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