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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:

Brake uneven wear of high-speed train intelligent monitoring using an ensemble model based on multi-sensor feature fusion and deep learning
Min Zhang, Xunjie Zhang, Jiliang Mo, et al.
Engineering Failure Analysis (2022) Vol. 137, pp. 106219-106219
Closed Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

AI for tribology: Present and future
Nian Yin, Pufan Yang, Songkai Liu, et al.
Friction (2024) Vol. 12, Iss. 6, pp. 1060-1097
Open Access | Times Cited: 17
Friction-induced vibration and noise characteristics, and interface tribological behavior during high-speed train braking: The effect of the residual height of the brake pad friction block
Z.Y. Xiang, J.K. Zhang, Songlan Xie, et al.
Wear (2023) Vol. 516-517, pp. 204619-204619
Closed Access | Times Cited: 19
Fault detection and diagnosis of air brake system: A systematic review
Zhe-Fan Hou, C.K.M. Lee, Yaqiong Lv, et al.
Journal of Manufacturing Systems (2023) Vol. 71, pp. 34-58
Closed Access | Times Cited: 17
Effect of uneven wear on the stability of friction braking system in high-speed train
Min Zhang, Shihao Xu, Jiliang Mo, et al.
Engineering Failure Analysis (2024) Vol. 158, pp. 108009-108009
Closed Access | Times Cited: 5
Friction-induced vibration and noise performance of high-speed train friction braking under the evolution of residual height of friction block
Z.Y. Xiang, Songlan Xie, S.J. Li, et al.
Tribology International (2023) Vol. 187, pp. 108770-108770
Closed Access | Times Cited: 13
Monitoring the deterioration state of braking friction performance of high-speed train under imbalanced data
Min Zhang, Wenxin Xu, Jiliang Mo, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 143, pp. 109939-109939
Closed Access
Intelligent recognition of tunnel lining defects based on deep learning: Methods, challenges and prospects
Zhong Zhou, Shishuai Li, Longbin Yan, et al.
Engineering Failure Analysis (2025), pp. 109332-109332
Closed Access
A Bayesian CNN-based fusion framework of sensor fault diagnosis
Beiyan He, Chunli Zhu, Zhongxiang Li, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 4, pp. 046110-046110
Closed Access | Times Cited: 3
Superimposable neural network for health monitoring of aircraft hydraulic system
Zhicen Song, Yunwen Feng, Cheng Lu
Engineering Failure Analysis (2024) Vol. 160, pp. 108063-108063
Closed Access | Times Cited: 3
Experimental study on the evolution of friction and wear behaviours of railway friction block during temperature rise under extreme braking conditions
C. Lu, Xinchi Jiang, Xiaoting Chen, et al.
Engineering Failure Analysis (2022) Vol. 141, pp. 106621-106621
Closed Access | Times Cited: 18
Deep subdomain generalisation network for health monitoring of high-speed train brake pads
Ruohui Hu, Min Zhang, Xiangyin Meng, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 113, pp. 104896-104896
Closed Access | Times Cited: 14
Diagnosis of brake friction faults in high-speed trains based on 1DCNN and GraphSAGE under data imbalance
Min Zhang, Xianjun Li, Zaiyu Xiang, et al.
Measurement (2022) Vol. 207, pp. 112378-112378
Closed Access | Times Cited: 12
Dynamic hybrid observer-based early slipping fault detection for high-speed train wheelsets
Shicai Yin, Tao Peng, Chao Yang, et al.
Control Engineering Practice (2023) Vol. 142, pp. 105736-105736
Closed Access | Times Cited: 5
The role of the damping component deformation in improving the tribological behavior at the high-speed train braking interface
Zaiyu Xiang, Songlan Xie, J.K. Zhang, et al.
Engineering Failure Analysis (2024) Vol. 162, pp. 108417-108417
Closed Access | Times Cited: 1
Friction performance prediction of automotive pads under operating conditions using attention-based CNN-BiLSTM deep learning framework
Xiaojing Yin, Sen Zhang, Bowen Zhang, et al.
Journal of Mechanical Science and Technology (2024) Vol. 38, Iss. 8, pp. 4135-4144
Closed Access | Times Cited: 1
State monitoring of brake uneven wear in high-speed train based on multi-source feature fusion
Min Zhang, Wenxin Xu, Jiamin Li, et al.
Structural Health Monitoring (2024)
Closed Access | Times Cited: 1
Condition prediction of submarine cable based on CNN-BiGRU integrating attention mechanism
Wei Yang, Bo Huang, Anan Zhang, et al.
Frontiers in Energy Research (2022) Vol. 10
Open Access | Times Cited: 7
Fault diagnosis of industrial robot gearbox using joint interclass and intraclass mappings
Shuai Yang, Lijie Kong, Ming Hou, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 11, pp. 115108-115108
Closed Access | Times Cited: 4
Research on the Gearbox Fault Diagnosis Method Based on Multi-Model Feature Fusion
Fengyun Xie, Hui Liu, Jiankun Dong, et al.
Machines (2022) Vol. 10, Iss. 12, pp. 1186-1186
Open Access | Times Cited: 4
Braking Friction Coefficient Prediction Using PSO–GRU Algorithm Based on Braking Dynamometer Testing
Shuwen Wang, Yang Yu, Shuangxia Liu, et al.
Lubricants (2024) Vol. 12, Iss. 6, pp. 195-195
Open Access
Rolling Bearings Fault Diagnosis Based on Two-stage Signal Fusion and Deep Multi-scale Multi-sensor Network
Zuozhou Pan, Yang Guan, Fengjie Fan, et al.
ISA Transactions (2024)
Closed Access
An experimental investigation on the tribological behavior of brake pads for high-speed trains in sandy environments
Bin Tang, Ruilan Tian, Z.Y. Xiang, et al.
Engineering Failure Analysis (2024) Vol. 166, pp. 108863-108863
Closed Access
Research on modeling method of providing oxygen functional architecture based on model
Hao Yang, Renyu Huang, Dongsheng Chen
Journal of Physics Conference Series (2024) Vol. 2882, Iss. 1, pp. 012011-012011
Open Access
SO-IMCKD processed signal improving MSCNN model’s fault diagnosis accuracy for drilling pump fluid end
Gang Li, Jiayao Hu, Yaping Ding, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 11, pp. 115115-115115
Closed Access | Times Cited: 1
Novel method for measuring a wear scar using deep learning
Sebin Lee, Taewan Kim, Seung‐Chul Lee, et al.
Tribology International (2023) Vol. 190, pp. 109043-109043
Open Access | Times Cited: 1
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