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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:

Discriminative feature learning and selection with label-induced sparse filtering for intelligent fault diagnosis of rotating machinery
Zhiqiang Zhang, Shuiqing Xu, Hongtian Chen
Mechanical Systems and Signal Processing (2023) Vol. 196, pp. 110338-110338
Closed Access | Times Cited: 9

Showing 9 citing articles:

Unsupervised feature learning using locality-preserved auto-encoder with complexity-invariant distance for intelligent fault diagnosis of machinery
Zhenghua Lu, Zhaobi Chu, Zhu Min, et al.
Applied Intelligence (2025) Vol. 55, Iss. 6
Closed Access
Temporally-preserving latent variable models: Offline and online training for reconstruction and interpretation of fault data for gearbox condition monitoring
Ryan Balshaw, P. Stephan Heyns, Daniël N. Wilke, et al.
Journal of Dynamics Monitoring and Diagnostics (2024)
Open Access | Times Cited: 3
Feature fusion and distillation embedded sparse Bayesian learning model for in-situ foreknowledge of robotic machining errors
Shengqiang Zhao, Hao Sun, Fangyu Peng, et al.
Journal of Manufacturing Systems (2023) Vol. 71, pp. 546-564
Closed Access | Times Cited: 7
Rolling bearing fault diagnosis based on the fusion of sparse filtering and discriminative domain adaptation method under multi-channel data-driven
Zonghao Jiao, Zhongwei Zhang, Youjia Li, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 066112-066112
Closed Access | Times Cited: 2
Deep discriminative sparse representation learning for machinery fault diagnosis
Renhe Yao, Hongkai Jiang, Wenxin Jiang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108836-108836
Closed Access | Times Cited: 2
A reusable decoder network penalized by smooth group lasso and its applications to large-scale fault diagnosis of machinery
Zhiqiang Zhang, Han He, Shuiqing Xu, et al.
Control Engineering Practice (2024) Vol. 153, pp. 106127-106127
Closed Access | Times Cited: 1
Deep Sparse Representation Classification for Aeroengine Inter-shaft Bearing Fault Diagnosis
Renhe Yao, Hongkai Jiang, Yunpeng Liu, et al.
(2024), pp. 167-173
Closed Access
Meta-Feature Encoding Based Mixed Domain Generalization Method for Machinery Fault Diagnosis Under Unseen Conditions
Shushuai Xie, Wei Cheng, Ji Xing, et al.
(2023)
Closed Access
Intelligent faults diagnostics of turbine vibration’s via Fourier transform and neuro-fuzzy systems with wavelets exploitation
Nadji Hadroug, Abdelhamid Iratni, Ahmed Hafaifa, et al.
Smart Science (2023) Vol. 12, Iss. 1, pp. 155-184
Closed Access
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