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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:

Intelligent fault diagnosis of rolling bearing based on wavelet transform and improved ResNet under noisy labels and environment
Pengfei Liang, Wenhui Wang, Xiaoming Yuan, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 115, pp. 105269-105269
Closed Access | Times Cited: 142

Showing 1-25 of 142 citing articles:

GTFE-Net: A Gramian Time Frequency Enhancement CNN for bearing fault diagnosis
Linshan Jia, Tommy W. S. Chow, Yixuan Yuan
Engineering Applications of Artificial Intelligence (2023) Vol. 119, pp. 105794-105794
Closed Access | Times Cited: 82
Fault transfer diagnosis of rolling bearings across multiple working conditions via subdomain adaptation and improved vision transformer network
Pengfei Liang, Zhuoze Yu, Bin Wang, et al.
Advanced Engineering Informatics (2023) Vol. 57, pp. 102075-102075
Closed Access | Times Cited: 70
Graph features dynamic fusion learning driven by multi-head attention for large rotating machinery fault diagnosis with multi-sensor data
Xin Zhang, Xi Zhang, Jie Liu, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 125, pp. 106601-106601
Closed Access | Times Cited: 44
Deep transfer learning strategy in intelligent fault diagnosis of rotating machinery
Shengnan Tang, Jingtao Ma, Zhengqi Yan, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108678-108678
Closed Access | Times Cited: 30
A Novel Transformer-based Few-Shot Learning Method for Intelligent Fault Diagnosis with Noisy Labels under Varying Working Conditions
Haoyu Wang, Chuanjiang Li, Peng Ding, et al.
Reliability Engineering & System Safety (2024) Vol. 251, pp. 110400-110400
Closed Access | Times Cited: 14
A nearly end-to-end deep learning approach to fault diagnosis of wind turbine gearboxes under nonstationary conditions
Liangwei Zhang, Qi Fan, Jing Lin, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 119, pp. 105735-105735
Closed Access | Times Cited: 65
Unsupervised fault diagnosis of wind turbine bearing via a deep residual deformable convolution network based on subdomain adaptation under time-varying speeds
Pengfei Liang, Bin Wang, Guoqian Jiang, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 118, pp. 105656-105656
Closed Access | Times Cited: 56
IFD-MDCN: Multibranch denoising convolutional networks with improved flow direction strategy for intelligent fault diagnosis of rolling bearings under noisy conditions
Sheng Li, Jinchen Ji, Yadong Xu, et al.
Reliability Engineering & System Safety (2023) Vol. 237, pp. 109387-109387
Open Access | Times Cited: 33
Bearing fault diagnosis based on CNN-BiLSTM and residual module
Guanghua Fu, Qingjuan Wei, Yongsheng Yang, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 12, pp. 125050-125050
Closed Access | Times Cited: 32
Triplet attention-enhanced residual tree-inspired decision network: A hierarchical fault diagnosis model for unbalanced bearing datasets
Lingli Cui, Zhilin Dong, Hai Xu, et al.
Advanced Engineering Informatics (2023) Vol. 59, pp. 102322-102322
Closed Access | Times Cited: 32
Simulation-Driven Subdomain Adaptation Network for bearing fault diagnosis with missing samples
Jianing Liu, Hongrui Cao, Shuaiming Su, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106201-106201
Closed Access | Times Cited: 29
Non-negative wavelet matrix factorization-based bearing fault intelligent classification method
Zhilin Dong, Dezun Zhao, Lingli Cui
Measurement Science and Technology (2023) Vol. 34, Iss. 11, pp. 115013-115013
Closed Access | Times Cited: 24
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
Multi-Techniques for Analyzing X-ray Images for Early Detection and Differentiation of Pneumonia and Tuberculosis Based on Hybrid Features
Ibrahim Abdulrab Ahmed, Ebrahim Mohammed Senan, Hamzeh Salameh Ahmad Shatnawi, et al.
Diagnostics (2023) Vol. 13, Iss. 4, pp. 814-814
Open Access | Times Cited: 22
A fault diagnosis for rolling bearing based on multilevel denoising method and improved deep residual network
Zhigang Feng, Shouqi Wang, Mingyue Yu
Digital Signal Processing (2023) Vol. 140, pp. 104106-104106
Closed Access | Times Cited: 21
Few-shot meta transfer learning-based damage detection of composite structures
Y.S. Chen, Xuebing Xu, Cheng Liu
Smart Materials and Structures (2024) Vol. 33, Iss. 2, pp. 025027-025027
Closed Access | Times Cited: 14
ReF-DDPM: A novel DDPM-based data augmentation method for imbalanced rolling bearing fault diagnosis
Yu Tian, Chaoshun Li, Jie Huang, et al.
Reliability Engineering & System Safety (2024) Vol. 251, pp. 110343-110343
Closed Access | Times Cited: 12
Fault vibration model driven fault-aware domain generalization framework for bearing fault diagnosis
Bin Pang, Qiuhai Liu, Zhenli Xu, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102620-102620
Closed Access | Times Cited: 11
Improved SE-ResNet Acoustic–Vibration Fusion for Rolling Bearing Composite Fault Diagnosis
Xiaojiao Gu, Yang Tian, Chi Li, et al.
Applied Sciences (2024) Vol. 14, Iss. 5, pp. 2182-2182
Open Access | Times Cited: 9
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
A novel approach for bearings multiclass fault diagnosis fusing multiscale deep convolution and hybrid attention networks
Fule Li, Xinlong Zhao
Measurement Science and Technology (2024) Vol. 35, Iss. 4, pp. 045017-045017
Closed 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
A Rolling Bearing Fault Diagnosis Method Based on the WOA-VMD and the GAT
Yaping Wang, Sheng Zhang, Ruofan Cao, et al.
Entropy (2023) Vol. 25, Iss. 6, pp. 889-889
Open Access | Times Cited: 20
Caputo-Fabrizio fractional order derivative stochastic resonance enhanced by ADOF and its application in fault diagnosis of wind turbine drivetrain
Xuefang Xu, Bo Li, Zijian Qiao, et al.
Renewable Energy (2023) Vol. 219, pp. 119398-119398
Closed Access | Times Cited: 20
CFI-LFENet: Infusing cross-domain fusion image and lightweight feature enhanced network for fault diagnosis
Chao Lian, Yuliang Zhao, Jinliang Shao, et al.
Information Fusion (2023) Vol. 104, pp. 102162-102162
Closed Access | Times Cited: 19
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