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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:

Cross-domain fault diagnosis of bearing using improved semi-supervised meta-learning towards interference of out-of-distribution samples
Jian Lin, Haidong Shao, Zhishan Min, et al.
Knowledge-Based Systems (2022) Vol. 252, pp. 109493-109493
Closed Access | Times Cited: 52

Showing 1-25 of 52 citing articles:

Generalized MAML for few-shot cross-domain fault diagnosis of bearing driven by heterogeneous signals
Jian Lin, Haidong Shao, Xiangdong Zhou, et al.
Expert Systems with Applications (2023) Vol. 230, pp. 120696-120696
Open Access | Times Cited: 118
Meta-learning with elastic prototypical network for fault transfer diagnosis of bearings under unstable speeds
Jingjie Luo, Haidong Shao, Jian Lin, et al.
Reliability Engineering & System Safety (2024) Vol. 245, pp. 110001-110001
Closed Access | Times Cited: 89
Maximum mean square discrepancy: A new discrepancy representation metric for mechanical fault transfer diagnosis
Quan Qian, Yi Wang, Taisheng Zhang, et al.
Knowledge-Based Systems (2023) Vol. 276, pp. 110748-110748
Closed Access | Times Cited: 82
Few-shot fault diagnosis of turnout switch machine based on semi-supervised weighted prototypical network
Zhenpeng Lao, Deqiang He, Zhenzhen Jin, et al.
Knowledge-Based Systems (2023) Vol. 274, pp. 110634-110634
Closed Access | Times Cited: 48
Application of deep learning to fault diagnosis of rotating machineries
Hao Su, Ling Xiang, Aijun Hu
Measurement Science and Technology (2024) Vol. 35, Iss. 4, pp. 042003-042003
Open Access | Times Cited: 15
Modified DSAN for unsupervised cross-domain fault diagnosis of bearing under speed fluctuation
Jingjie Luo, Haidong Shao, Hongru Cao, et al.
Journal of Manufacturing Systems (2022) Vol. 65, pp. 180-191
Open Access | Times Cited: 45
Semi-supervised learning for industrial fault detection and diagnosis: A systemic review
José Miguel Ramírez‐Sanz, Jose-Alberto Maestro-Prieto, Álvar Arnaiz‐González, et al.
ISA Transactions (2023) Vol. 143, pp. 255-270
Open Access | Times Cited: 36
Cross-domain few-shot fault diagnosis based on meta-learning and domain adversarial graph convolutional network
Junwei Hu, Weigang Li, Yong Zhang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 136, pp. 108970-108970
Closed Access | Times Cited: 13
A novel semi-supervised prototype network with two-stream wavelet scattering convolutional encoder for TBM main bearing few-shot fault diagnosis
Xingchen Fu, Jianfeng Tao, Keming Jiao, et al.
Knowledge-Based Systems (2024) Vol. 286, pp. 111408-111408
Closed Access | Times Cited: 9
Few-Shot Bearing Fault Diagnosis via Ensembling Transformer-based Model with Mahalanobis Distance Metric Learning from Multiscale Features
Manh-Hung Vu, Van-Quang Nguyen, Thi-Thao Tran, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-18
Closed Access | Times Cited: 9
A holistic semi-supervised method for imbalanced fault diagnosis of rotational machinery with out-of-distribution samples
Zhangjun Wu, Renli Xu, Yuansheng Luo, et al.
Reliability Engineering & System Safety (2024) Vol. 250, pp. 110297-110297
Closed Access | Times Cited: 9
Few-shot remaining useful life prediction based on meta-learning with deep sparse kernel network
Jing Yang, Xiaomin Wang, Zhipeng Luo
Information Sciences (2023) Vol. 653, pp. 119795-119795
Closed Access | Times Cited: 17
Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis
Hao Lü, Adam Thelen, Olga Fink, et al.
Mechanical Systems and Signal Processing (2024) Vol. 210, pp. 111068-111068
Open Access | Times Cited: 7
A Semi-supervised Gaussian Mixture Variational Autoencoder method for few-shot fine-grained fault diagnosis
Zhiqian Zhao, Yeyin Xu, Jiabin Zhang, et al.
Neural Networks (2024) Vol. 178, pp. 106482-106482
Closed Access | Times Cited: 5
A novel meta-learning network with adversarial domain-adaptation and attention mechanism for cross-domain for train bearing fault diagnosis
Hao Zhong, Deqiang He, Zexian Wei, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 12, pp. 125109-125109
Closed Access | Times Cited: 5
A meta-learning network with anti-interference for few-shot fault diagnosis
Zhiqian Zhao, Runchao Zhao, Xianglin Wu, et al.
Neurocomputing (2023) Vol. 552, pp. 126551-126551
Closed Access | Times Cited: 14
Triplet adversarial Learning-driven graph architecture search network augmented with Probsparse-attention mechanism for fault diagnosis under Few-shot & Domain-shift
Yuanhong Chang, Jinglong Chen, Weiguang Zheng, et al.
Mechanical Systems and Signal Processing (2023) Vol. 199, pp. 110462-110462
Closed Access | Times Cited: 13
Health prognosis of bearings based on transferable autoregressive recurrent adaptation with few-shot learning
Jichao Zhuang, Minping Jia, Cheng‐Geng Huang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 211, pp. 111186-111186
Closed Access | Times Cited: 4
Semi-supervised diagnosis of wind-turbine gearbox misalignment and imbalance faults
P. Maestro, José Miguel Ramírez‐Sanz, Andrés Bustillo, et al.
Applied Intelligence (2024) Vol. 54, Iss. 6, pp. 4525-4544
Open Access | Times Cited: 4
Few-shot bearing fault diagnosis by semi-supervised meta-learning with graph convolutional neural network under variable working conditions
Zhen Liu, Zhenrui Peng
Measurement (2024) Vol. 240, pp. 115402-115402
Closed Access | Times Cited: 4
Deep Learning in Industrial Machinery: A Critical Review of Bearing Fault Classification Methods
Attiq Ur Rehman, Weidong Jiao, Yonghua Jiang, et al.
Applied Soft Computing (2025), pp. 112785-112785
Closed Access
A dynamic weighted joint distribution domain adaptation network for cross-machine fault diagnosis of rolling bearings
Qi Chang, Congcong Fang, Longqing Fan, et al.
Structural Health Monitoring (2025)
Closed Access
KMDSAN: A novel method for cross-domain and unsupervised bearing fault diagnosis
Shuping Wu, Peiming Shi, Xuefang Xu, et al.
Knowledge-Based Systems (2025), pp. 113170-113170
Closed Access
A pruning-aware dynamic slimmable network using meta-gradients for high-speed train bogie bearing fault diagnosis
Jingsong Xie, S. Cao, Tongyang Pan, et al.
ISA Transactions (2025)
Closed Access
Intelligent fault classification of air compressors using Harris hawks optimization and machine learning algorithms
Adel Afia, Fawzi Gougam, Chemseddine Rahmoune, et al.
Transactions of the Institute of Measurement and Control (2023) Vol. 46, Iss. 2, pp. 359-378
Closed Access | Times Cited: 10
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