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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 novel transfer learning method for robust fault diagnosis of rotating machines under variable working conditions
Weiwei Qian, Shunming Li, Pengxing Yi, et al.
Measurement (2019) Vol. 138, pp. 514-525
Open Access | Times Cited: 145

Showing 1-25 of 145 citing articles:

Intelligent fault diagnosis of machines with small & imbalanced data: A state-of-the-art review and possible extensions
Tianci Zhang, Jinglong Chen, Fudong Li, et al.
ISA Transactions (2021) Vol. 119, pp. 152-171
Closed Access | Times Cited: 368
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
Applications of Unsupervised Deep Transfer Learning to Intelligent Fault Diagnosis: A Survey and Comparative Study
Zhibin Zhao, Qiyang Zhang, Xiaolei Yu, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-28
Open Access | Times Cited: 329
Intelligent fault diagnosis of rolling bearings based on normalized CNN considering data imbalance and variable working conditions
Bo Zhao, Xianmin Zhang, Hai Li, et al.
Knowledge-Based Systems (2020) Vol. 199, pp. 105971-105971
Closed Access | Times Cited: 299
An adaptive deep transfer learning method for bearing fault diagnosis
Zhenghong Wu, Hongkai Jiang, Ke Zhao, et al.
Measurement (2019) Vol. 151, pp. 107227-107227
Closed Access | Times Cited: 238
Transfer fault diagnosis of bearing installed in different machines using enhanced deep auto-encoder
Zhiyi He, Haidong Shao, Jing Lin, et al.
Measurement (2019) Vol. 152, pp. 107393-107393
Closed Access | Times Cited: 232
Deep Learning-Based Intelligent Fault Diagnosis Methods Toward Rotating Machinery
Shengnan Tang, Shouqi Yuan, Yong Zhu
IEEE Access (2019) Vol. 8, pp. 9335-9346
Open Access | Times Cited: 224
Deep transfer multi-wavelet auto-encoder for intelligent fault diagnosis of gearbox with few target training samples
Zhiyi He, Haidong Shao, Ping Wang, et al.
Knowledge-Based Systems (2019) Vol. 191, pp. 105313-105313
Closed Access | Times Cited: 202
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: 190
Intelligent fault diagnosis of rotating machinery via wavelet transform, generative adversarial nets and convolutional neural network
Pengfei Liang, Chao Deng, Jun Wu, et al.
Measurement (2020) Vol. 159, pp. 107768-107768
Closed Access | Times Cited: 178
Cross-Domain Fault Diagnosis Using Knowledge Transfer Strategy: A Review
Huailiang Zheng, Rixin Wang, Yuantao Yang, et al.
IEEE Access (2019) Vol. 7, pp. 129260-129290
Open Access | Times Cited: 164
A Review of Artificial Intelligence Methods for Condition Monitoring and Fault Diagnosis of Rolling Element Bearings for Induction Motor
Omar AlShorman, Muhammad Irfan, Nordin Saad, et al.
Shock and Vibration (2020) Vol. 2020, pp. 1-20
Open Access | Times Cited: 163
Machine Learning Approach Using MLP and SVM Algorithms for the Fault Prediction of a Centrifugal Pump in the Oil and Gas Industry
Pier Francesco Orrù, Andrea Zoccheddu, Lorenzo Sassu, et al.
Sustainability (2020) Vol. 12, Iss. 11, pp. 4776-4776
Open Access | Times Cited: 156
A systematic review of rolling bearing fault diagnoses based on deep learning and transfer learning: Taxonomy, overview, application, open challenges, weaknesses and recommendations
Mohammed Hakim, Abdoulhdi A. Borhana Omran, Ali Najah Ahmed, et al.
Ain Shams Engineering Journal (2022) Vol. 14, Iss. 4, pp. 101945-101945
Open Access | Times Cited: 134
Wind turbine fault diagnosis based on transfer learning and convolutional autoencoder with small-scale data
Yanting Li, Wenbo Jiang, Guangyao Zhang, et al.
Renewable Energy (2021) Vol. 171, pp. 103-115
Closed Access | Times Cited: 119
Domain adaptation network base on contrastive learning for bearings fault diagnosis under variable working conditions
Yiyao An, Ke Zhang, Yi Chai, et al.
Expert Systems with Applications (2022) Vol. 212, pp. 118802-118802
Closed Access | Times Cited: 104
Domain generalization for cross-domain fault diagnosis: An application-oriented perspective and a benchmark study
Chao Zhao, Enrico Zio, Weiming Shen
Reliability Engineering & System Safety (2024) Vol. 245, pp. 109964-109964
Closed Access | Times Cited: 77
A systematic literature review of deep learning for vibration-based fault diagnosis of critical rotating machinery: Limitations and challenges
Omri Matania, Itai Dattner, Jacob Bortman, et al.
Journal of Sound and Vibration (2024) Vol. 590, pp. 118562-118562
Closed 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 lightweight neural network with strong robustness for bearing fault diagnosis
Dechen Yao, Hengchang Liu, Jianwei Yang, et al.
Measurement (2020) Vol. 159, pp. 107756-107756
Closed Access | Times Cited: 116
Challenges and Opportunities of AI-Enabled Monitoring, Diagnosis & Prognosis: A Review
Zhibin Zhao, Jingyao Wu, Tianfu Li, et al.
Chinese Journal of Mechanical Engineering (2021) Vol. 34, Iss. 1
Open Access | Times Cited: 98
Enhanced K-Nearest Neighbor for Intelligent Fault Diagnosis of Rotating Machinery
Jiantao Lu, Weiwei Qian, Shunming Li, et al.
Applied Sciences (2021) Vol. 11, Iss. 3, pp. 919-919
Open Access | Times Cited: 91
Hybrid distance-guided adversarial network for intelligent fault diagnosis under different working conditions
Baokun Han, Xiao Zhang, Jinrui Wang, et al.
Measurement (2021) Vol. 176, pp. 109197-109197
Closed Access | Times Cited: 87
Joint distribution adaptation with diverse feature aggregation: A new transfer learning framework for bearing diagnosis across different machines
Shiyao Jia, Yafei Deng, Jun Lv, et al.
Measurement (2021) Vol. 187, pp. 110332-110332
Closed Access | Times Cited: 87
Intelligent Fault Diagnosis of Rotary Machines: Conditional Auxiliary Classifier GAN Coupled With Meta Learning Using Limited Data
Sonal Dixit, Nishchal K. Verma, A. K. Ghosh
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-11
Closed Access | Times Cited: 86
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