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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 novel method based on meta-learning for bearing fault diagnosis with small sample learning under different working conditions
Hao Su, Ling Xiang, Aijun Hu, et al.
Mechanical Systems and Signal Processing (2022) Vol. 169, pp. 108765-108765
Closed Access | Times Cited: 164

Showing 1-25 of 164 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
A time-frequency spectral amplitude modulation method and its applications in rolling bearing fault diagnosis
Zuhua Jiang, Kun Zhang, Ling Xiang, et al.
Mechanical Systems and Signal Processing (2022) Vol. 185, pp. 109832-109832
Closed Access | Times Cited: 86
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
Prediction of bearing remaining useful life based on DACN-ConvLSTM model
Guopeng Zhu, Zening Zhu, Ling Xiang, et al.
Measurement (2023) Vol. 211, pp. 112600-112600
Closed Access | Times Cited: 40
Faulty rolling bearing digital twin model and its application in fault diagnosis with imbalanced samples
Yi Qin, Hongyu Liu, Yongfang Mao
Advanced Engineering Informatics (2024) Vol. 61, pp. 102513-102513
Closed Access | Times Cited: 29
Rolling bearing fault diagnosis method based on improved residual shrinkage network
Linjun Wang, Tengxiao Zou, Kanglin Cai, et al.
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2024) Vol. 46, Iss. 3
Closed Access | Times Cited: 25
A new multi-source information domain adaption network based on domain attributes and features transfer for cross-domain fault diagnosis
Yue Yu, Hamid Reza Karimi, Peiming Shi, et al.
Mechanical Systems and Signal Processing (2024) Vol. 211, pp. 111194-111194
Open Access | Times Cited: 20
An information fusion-based meta transfer learning method for few-shot fault diagnosis under varying operating conditions
Cuiying Lin, Yun Kong, Qinkai Han, et al.
Mechanical Systems and Signal Processing (2024) Vol. 220, pp. 111652-111652
Closed Access | Times Cited: 17
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
Toward accurate extraction of bearing fault modulation characteristics with novel time–frequency modulation bispectrum and modulation Gini index analysis
Xue Zou, Huaming Zhang, Zuhua Jiang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 219, pp. 111629-111629
Closed Access | Times Cited: 15
Knowledge Embedded Autoencoder Network for Harmonic Drive Fault Diagnosis Under Few-Shot Industrial Scenarios
Jiaxian Chen, Kairu Wen, Jingyan Xia, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 13, pp. 22915-22925
Closed Access | Times Cited: 14
Frequency slice graph spectrum model and its application in bearing fault feature extraction
Kun Zhang, Yanlei Liu, Long Zhang, et al.
Mechanical Systems and Signal Processing (2025) Vol. 226, pp. 112383-112383
Closed Access | Times Cited: 4
Feature identification based on cepstrum-assisted frequency slice function for bearing fault diagnosis
C. Ma, Wenxu Zhang, Mengdi Shi, et al.
Measurement (2025), pp. 116753-116753
Closed Access | Times Cited: 1
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
Fault diagnosis of rotating machinery based on graph weighted reinforcement networks under small samples and strong noise
Xiaoxia Yu, Baoping Tang, Lei Deng
Mechanical Systems and Signal Processing (2022) Vol. 186, pp. 109848-109848
Closed Access | Times Cited: 50
A class alignment method based on graph convolution neural network for bearing fault diagnosis in presence of missing data and changing working conditions
Mohammadreza Kavianpour, Amin Ramezani, Mohammad Taghi Hamidi Beheshti
Measurement (2022) Vol. 199, pp. 111536-111536
Closed Access | Times Cited: 41
An effective fault diagnosis approach for bearing using stacked de-noising auto-encoder with structure adaptive adjustment
Lerui Chen, Yidan Ma, Heyu Hu, et al.
Measurement (2023) Vol. 214, pp. 112774-112774
Closed Access | Times Cited: 36
Attention-Embedded Quadratic Network (Qttention) for Effective and Interpretable Bearing Fault Diagnosis
Jing-Xiao Liao, Hangcheng Dong, Zhi-Qi Sun, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-13
Open Access | Times Cited: 32
Graph neural network architecture search for rotating machinery fault diagnosis based on reinforcement learning
Jialin Li, Xuan Cao, Renxiang Chen, et al.
Mechanical Systems and Signal Processing (2023) Vol. 202, pp. 110701-110701
Closed Access | Times Cited: 29
Rolling Bearing Fault Diagnosis Method Based on Self-Calibrated Coordinate Attention Mechanism and Multi-Scale Convolutional Neural Network Under Small Samples
Linlin Xue, Chunli Lei, Mengxuan Jiao, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 9, pp. 10206-10214
Closed Access | Times Cited: 27
Transformer-based meta learning method for bearing fault identification under multiple small sample conditions
Xianze Li, Hao Su, Ling Xiang, et al.
Mechanical Systems and Signal Processing (2023) Vol. 208, pp. 110967-110967
Closed Access | Times Cited: 25
TSN: A novel intelligent fault diagnosis method for bearing with small samples under variable working conditions
Peiming Shi, Shuping Wu, Xuefang Xu, et al.
Reliability Engineering & System Safety (2023) Vol. 240, pp. 109575-109575
Closed Access | Times Cited: 23
A two-stage domain alignment method for multi-source domain fault diagnosis
Wei Cao, Zong Meng, Dengyun Sun, et al.
Measurement (2023) Vol. 214, pp. 112818-112818
Closed Access | Times Cited: 22
Research on Fault Diagnosis of Rolling Bearing Based on Lightweight Model With Multiscale Features
Zong Meng, Cheng Luo, Jimeng Li, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 12, pp. 13236-13247
Closed Access | Times Cited: 21
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