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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:

Untrained Compound Fault Diagnosis for Planetary Gearbox Based on Adaptive Learning VMD and DSSECNN
Xiaojia Kong, Liang Meng, Yuanhao Su, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 11, pp. 11838-11854
Closed Access | Times Cited: 15

Showing 15 citing articles:

Compound fault diagnosis of diesel engines by combining generative adversarial networks and transfer learning
Zhiquan Cui, Yanlin Lu, Yan Xu, et al.
Expert Systems with Applications (2024) Vol. 251, pp. 123969-123969
Closed Access | Times Cited: 10
Feature Entropy Recognition Based on Dual-Channel-Multi-Scale 1DCNN Model for Intelligent Compound Fault Diagnosis of Bearings
Chunlin Li, Qintai Hu, Jianbin Xiong, et al.
IEEE Transactions on Instrumentation and Measurement (2025) Vol. 74, pp. 1-14
Closed Access
A gearbox fault diagnosis method based on Swin Transformer and Markov transform fields
Jiangran Liu, Rujiang Hao, Feiyue Deng, et al.
Engineering Research Express (2025) Vol. 7, Iss. 1, pp. 015225-015225
Closed Access
Compound damage detection using wavelet transform and deep neural network trained on healthy and single damage states: Validation on a laboratory-scale offshore jacket model
Wei-Qiang Feng, Zohreh Mousavi, Jian‐Fu Lin, et al.
Structural Health Monitoring (2025)
Closed Access
Residual attention temporal recurrent network for fault diagnosis of gearboxes under limited labeled data
Jichao Zhuang, Jianhai Yan, Cheng‐Geng Huang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 129, pp. 107539-107539
Closed Access | Times Cited: 12
Deep exponential excitation networks: toward stronger attention mechanism for weak fault diagnosis
Baihong Zhong, Minghang Zhao, Shisheng Zhong, et al.
Structural Health Monitoring (2024) Vol. 23, Iss. 6, pp. 3850-3866
Closed Access | Times Cited: 4
A Mixed-feed Identification Method for Sizer Crusher Based on Squeeze-and-excitation Residual Network
Yankun Bi, Yongtai Pan, Guohua Li
IEEE Sensors Journal (2024) Vol. 24, Iss. 13, pp. 21706-21718
Closed Access | Times Cited: 1
Planetary gearbox fault classification based on tooth root strain and GAF pseudo images
Dongyang Hu, Hang Niu, Guang Wang, et al.
ISA Transactions (2024) Vol. 153, pp. 490-503
Closed Access | Times Cited: 1
A hybrid wavelet-deep learning approach for vibration-based damage detection in monopile offshore structures considering soil interaction
Wei-Qiang Feng, Zohreh Mousavi, Mohammadreza Farhadi, et al.
Journal of Civil Structural Health Monitoring (2024)
Closed Access | Times Cited: 1
Bearing compound fault diagnosis using energy-constrained swarm decomposition and adaptive spectral amplitude modulation
Chaoang Xiao, Pu Yang, Yue Shang, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 11, pp. 18172-18184
Closed Access | Times Cited: 1
SPLSTM: A Prediction Model for Operational Faults in Rotating Machinery
Xiaosheng Lan, Tongle Xu
IEEE Sensors Journal (2024) Vol. 24, Iss. 7, pp. 10447-10461
Closed Access
Fault Types and Sizes Recognition of Rolling Bearing Based on Multi-Task Semi-Supervised Learning
Ziyue Jiang, Jianbo Yu
IEEE Sensors Journal (2024) Vol. 24, Iss. 11, pp. 17907-17916
Closed Access
An Intelligent Compound Fault Diagnosis Method Using Generalized Zero-shot Model of Bearing
Jian Cen, Bichuang Zhao, Xi Liu, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 9, pp. 096134-096134
Closed Access
Adaptive mode decomposition method based on fault feature orientation and its application to compound fault diagnosis of planetary gearboxes
Hongkun Li, Shunxin Cao, Kongliang Zhang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 10, pp. 106104-106104
Closed Access
Deep learning-based fault diagnosis of planetary gearbox: A systematic review
Hassaan Ahmad, Wei Cheng, Ji Xing, et al.
Journal of Manufacturing Systems (2024) Vol. 77, pp. 730-745
Closed Access
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