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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:

A wavelet packet transform-based deep feature transfer learning method for bearing fault diagnosis under different working conditions
Xiao Yu, Zhongting Liang, Youjie Wang, et al.
Measurement (2022) Vol. 201, pp. 111597-111597
Open Access | Times Cited: 64

Showing 1-25 of 64 citing articles:

Semisupervised Subdomain Adaptation Graph Convolutional Network for Fault Transfer Diagnosis of Rotating Machinery Under Time-Varying Speeds
Pengfei Liang, Leitao Xu, Hanqin Shuai, et al.
IEEE/ASME Transactions on Mechatronics (2023) Vol. 29, Iss. 1, pp. 730-741
Closed Access | Times Cited: 47
An Adaptive Domain Adaptation Method for Rolling Bearings’ Fault Diagnosis Fusing Deep Convolution and Self-Attention Networks
Xiao Yu, Youjie Wang, Zhongting Liang, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-14
Closed Access | Times Cited: 45
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
Interpretable physics-informed domain adaptation paradigm for cross-machine transfer diagnosis
Chao He, Hongmei Shi, Xiaorong Liu, et al.
Knowledge-Based Systems (2024) Vol. 288, pp. 111499-111499
Closed Access | Times Cited: 20
Conditional distribution-guided adversarial transfer learning network with multi-source domains for rolling bearing fault diagnosis
Zhenghong Wu, Hongkai Jiang, Shaowei Liu, et al.
Advanced Engineering Informatics (2023) Vol. 56, pp. 101993-101993
Closed Access | Times Cited: 31
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
Bearing faults classification using a new approach of signal processing combined with machine learning algorithms
Fawzi Gougam, Adel Afia, Abdenour Soualhi, et al.
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2024) Vol. 46, Iss. 2
Closed Access | Times Cited: 9
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
Unsupervised incremental transfer learning with knowledge distillation for online remaining useful life prediction of rotating machinery
Yunjia Liang, Wentao Mao, Chao Wu
Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability (2024)
Closed Access | Times Cited: 6
Domain adaptation with domain specific information and feature disentanglement for bearing fault diagnosis
Shaozhang Xie, Peng Xia, Hanqi Zhang
Measurement Science and Technology (2024) Vol. 35, Iss. 5, pp. 056101-056101
Open Access | Times Cited: 5
Transfer Learning for Prognostics and Health Management: Advances, Challenges, and Opportunities
Ruqiang Yan, Weihua Li, Siliang Lu, et al.
Journal of Dynamics Monitoring and Diagnostics (2024)
Open Access | Times Cited: 5
Deep learning based approaches for intelligent industrial machinery health management and fault diagnosis in resource-constrained environments
Ali Saeed, Muazzam A. Khan, Usman Akram, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Data-driven machinery fault diagnosis: A comprehensive review
Dhiraj Neupane, Mohamed Reda Bouadjenek, Richard Dazeley, et al.
Neurocomputing (2025), pp. 129588-129588
Open Access
Multi-sensor fusion rolling bearing intelligent fault diagnosis based on VMD and ultra-lightweight GoogLeNet in industrial environments
Shouqi Wang, Zhigang Feng
Digital Signal Processing (2023) Vol. 145, pp. 104306-104306
Closed Access | Times Cited: 15
A novel hierarchical training architecture for Siamese Neural Network based fault diagnosis method under small sample
Juanru Zhao, Yuan Mei, Jin Cui, et al.
Measurement (2023) Vol. 215, pp. 112851-112851
Closed Access | Times Cited: 14
Wavelet Packet Transform and Deep Learning-based Fusion of Audio-Visual Signals: A Novel Approach for Enhancing Laser Cleaning Effect Evaluation
Haipeng Huang, Liang Li, Shiwei Liu, et al.
International Journal of Precision Engineering and Manufacturing-Green Technology (2024) Vol. 11, Iss. 4, pp. 1263-1278
Closed Access | Times Cited: 4
MGTN-DSI: A multi-sensor graph transfer network considering dual structural information for fault diagnosis under varying working conditions
Jianjie Liu, Xianfeng Yuan, Xilin Yang, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103119-103119
Closed Access
Prediction Model for Newly-Added Sensors to Ocean Buoys: Leveraging Adversarial Loss and Deep Residual LSTM Architecture
Qiguang Zhu, Zhen Shen, Wenjing Qiao, et al.
Digital Signal Processing (2025), pp. 105126-105126
Closed Access
Deep time–frequency learning for interpretable weak signal enhancement of rotating machineries
Jiakai Ding, Yi Wang, Yi Qin, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 124, pp. 106598-106598
Closed Access | Times Cited: 12
Prognostics and health management for induction machines: a comprehensive review
Chao Huang, Siqi Bu, Hiu Hung Lee, et al.
Journal of Intelligent Manufacturing (2023) Vol. 35, Iss. 3, pp. 937-962
Closed Access | Times Cited: 11
Real-time bearing fault classification of induction motor using enhanced inception ResNet-V2
Karan Kumar K, Srihari Mandava
Applied Artificial Intelligence (2024) Vol. 38, Iss. 1
Open Access | Times Cited: 3
An adaptive few-shot fault diagnosis method based on virtual samples generated by fault characteristics of rotating machines
Peng Wu, Gongye Yu, Qianqian Yu, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 136, pp. 109017-109017
Closed Access | Times Cited: 3
A Novel Fault Diagnosis of a Rolling Bearing Method Based on Variational Mode Decomposition and an Artificial Neural Network
Xiaobei Liang, Jinyong Yao, Weifang Zhang, et al.
Applied Sciences (2023) Vol. 13, Iss. 6, pp. 3413-3413
Open Access | Times Cited: 10
Data augmentation on fault diagnosis of wind turbine gearboxes with an enhanced flow-based generative model
Wenliao Du, Pengxiang Zhu, Ziqiang Pu, et al.
Measurement (2023) Vol. 225, pp. 113985-113985
Closed Access | Times Cited: 9
Stacked maximum independence autoencoders: A domain generalization approach for fault diagnosis under various working conditions
Shan Pang
Mechanical Systems and Signal Processing (2023) Vol. 208, pp. 111035-111035
Closed Access | Times Cited: 9
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