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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 hybrid intelligent rolling bearing fault diagnosis method combining WKN-BiLSTM and attention mechanism
Jiang Wang, Junyu Guo, Lin Wang, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 8, pp. 085106-085106
Closed Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

A deep feature learning method for remaining useful life prediction of drilling pumps
Junyu Guo, Jia‐Lun Wan, Yan Yang, et al.
Energy (2023) Vol. 282, pp. 128442-128442
Closed Access | Times Cited: 54
A parallel deep neural network for intelligent fault diagnosis of drilling pumps
Junyu Guo, Yulai Yang, He Li, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108071-108071
Open Access | Times Cited: 43
A hybrid fault diagnosis scheme for milling tools using MWN-CBAM-PatchTST network with acoustic emission signals
Junyu Guo, Hongyun Luo, Yongming Xing, et al.
Nondestructive Testing And Evaluation (2025), pp. 1-29
Closed Access | Times Cited: 1
A deep learning based health indicator construction and fault prognosis with uncertainty quantification for rolling bearings
Zhiyuan Wang, Junyu Guo, Jiang Wang, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 10, pp. 105105-105105
Closed Access | Times Cited: 22
A hybrid deep learning model towards fault diagnosis of drilling pump
Junyu Guo, Yulai Yang, He Li, et al.
Applied Energy (2024) Vol. 372, pp. 123773-123773
Open Access | Times Cited: 12
Review of research on signal decomposition and fault diagnosis of rolling bearing based on vibration signal
Junning Li, Luo Wen-guang, Mengsha Bai
Measurement Science and Technology (2024) Vol. 35, Iss. 9, pp. 092001-092001
Closed Access | Times Cited: 9
Fault Diagnosis Method for Bearing Based on Attention Mechanism and Multi-Scale Convolutional Neural Network
Qimin Shen, Zengqiang Zhang
IEEE Access (2024) Vol. 12, pp. 12940-12952
Open Access | Times Cited: 8
Rolling bearing fault diagnosis based on multiple wavelet coefficient dimensionality reduction and improved residual network
Xiaoyang Zheng, Peixi Yang, Kai Yan, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108087-108087
Closed Access | Times Cited: 7
Remaining useful life prediction of rolling bearings based on TCN-MSA
Guang‐Jun Jiang, Zheng-Wei Duan, Qi Zhao, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 2, pp. 025125-025125
Closed Access | Times Cited: 18
Bayesian Fusion of Degradation and Failure Time Data for Reliability Assessment of Industrial Equipment Considering Individual Differences
Guo‐Zhong Fu, Xian Zhang, Wei Li, et al.
Processes (2024) Vol. 12, Iss. 2, pp. 268-268
Open Access | Times Cited: 6
A hybrid fault diagnosis method for rolling bearings based on GGRU-1DCNN with AdaBN algorithm under multiple load conditions
Lirong Sun, Xiaomin Zhu, Jiannan Xiao, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 7, pp. 076201-076201
Closed Access | Times Cited: 4
Bearing fault diagnosis based on high-confidence pseudo-labels and dual-view multi-adversarial sparse joint attention network under variable working conditions
Cailu Pan, Zhiwu Shang, Wanxiang Li, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108625-108625
Closed Access | Times Cited: 4
A novel rolling bearing fault diagnosis method based on time-series fusion transformer with interpretability analysis
You Keshun, Lian Zengwei, Ronghua Chen, et al.
Nondestructive Testing And Evaluation (2024), pp. 1-27
Closed Access | Times Cited: 3
A reliability analysis and optimization method for a turbine shaft under combined high and low cycle fatigue loading
Song Bai, Ying Zeng, Tudi Huang, et al.
Quality and Reliability Engineering International (2024) Vol. 40, Iss. 5, pp. 2367-2380
Closed Access | Times Cited: 2
Design of a progressive fault diagnosis system for hydropower units considering unknown faults
Jinbao Chen, Yang Zheng, Xiaoqin Deng, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 015904-015904
Closed Access | Times Cited: 5
A hierarchical transformer-based adaptive metric and joint-learning network for few-shot rolling bearing fault diagnosis
Zong Meng, Zhaohui Zhang, Yang Guan, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 3, pp. 035114-035114
Closed Access | Times Cited: 5
Diagnosis of Multiple Open-Circuit Faults in Three-Phase Induction Machine Drive Systems Based on Bidirectional Long Short-Term Memory Algorithm
Badii Gmati, Amine Ben Rhouma, Houda Meddeb, et al.
World Electric Vehicle Journal (2024) Vol. 15, Iss. 2, pp. 53-53
Open Access | Times Cited: 1
Multiscale ECA network: a rotation mechanical domain adaptation method with minimal class confusion
Xueyi Li, Tianyu Yu, Kaiyu Su, et al.
Structural Health Monitoring (2024)
Closed Access | Times Cited: 1
Degradation Indicator Construction Using Dual-Class Component Feature Fusion Recalibration for Bearing Performance Evaluation
Yuanyuan Zhou, Hang Wang, Yongbin Liu, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 20, pp. 24849-24861
Closed Access | Times Cited: 4
A Meta-Heuristic Sustainable Intelligent Internet of Things Framework for Bearing Fault Diagnosis of Electric Motor under Variable Load Conditions
Swarnali Deb Bristi, Mehtar Jahin Tatha, Md. Firoj Ali, et al.
Sustainability (2023) Vol. 15, Iss. 24, pp. 16722-16722
Open Access | Times Cited: 3
An intelligent feature recognition method of natural gas pipelines based on shapelet and blending fusion model
Tingxia Ma, Hu Cheng, Lin Wang, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 015004-015004
Closed Access | Times Cited: 2
WBUN: An interpretable convolutional neural network with wavelet basis unit embedded for fault diagnosis
Sen Gao, Zhijin Zhang, Xin Zhang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 8, pp. 086125-086125
Open Access
Rolling Bearing Fault Diagnosis Method Based on Wavelet Time–Frequency Map and Improved ConvNext
Feifan Qin, Chao Zhang, Jianguo Wang, et al.
Mechanisms and machine science (2024), pp. 149-160
Closed Access
A hybrid deep learning network for diagnosing multipoint faults in rolling bearings under variable operating conditions
Y. Huang, Changfeng Yan, Bin Liu, et al.
Journal of Mechanical Science and Technology (2024) Vol. 38, Iss. 11, pp. 5989-6003
Closed Access
Fault Diagnosis Method for Hydropower Station Measurement and Control System Based on ISSA-VMD and 1DCNN-BiLSTM
Lin Wang, Fangqing Zhang, Jiefei Wang, et al.
Energies (2024) Vol. 17, Iss. 22, pp. 5686-5686
Open Access
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