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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:

Bearing fault diagnosis method based on a multi-head graph attention network
Li Jiang, Xingjie Li, Lin Wu, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 7, pp. 075012-075012
Closed Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

Attention mechanism in intelligent fault diagnosis of machinery: A review of technique and application
Haixin Lv, Jinglong Chen, Tongyang Pan, et al.
Measurement (2022) Vol. 199, pp. 111594-111594
Closed Access | Times Cited: 148
Planetary gearbox fault diagnosis based on FDKNN-DGAT with few labeled data
Hongfeng Tao, Haojin Shi, Jier Qiu, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 2, pp. 025036-025036
Closed Access | Times Cited: 60
An improved GNN using dynamic graph embedding mechanism: A novel end-to-end framework for rolling bearing fault diagnosis under variable working conditions
Zidong Yu, Changhe Zhang, Chao Deng
Mechanical Systems and Signal Processing (2023) Vol. 200, pp. 110534-110534
Closed Access | Times Cited: 54
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: 42
Deep Learning-Based Bearing Fault Diagnosis Using a Trusted Multiscale Quadratic Attention-Embedded Convolutional Neural Network
Yuheng Tang, Chaoyong Zhang, Jianzhao Wu, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-15
Closed Access | Times Cited: 19
A pruned-optimized weighted graph convolutional network for axial flow pump fault diagnosis with hydrophone signals
Xin Zhang, Li Jiang, Lei Wang, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102365-102365
Closed Access | Times Cited: 17
A sound-vibration physical-information fusion constraint-guided deep learning method for rolling bearing fault diagnosis
You Keshun, Wang Puzhou, Peng Huang, et al.
Reliability Engineering & System Safety (2024), pp. 110556-110556
Closed Access | Times Cited: 9
Transfer learning rolling bearing fault diagnosis model based on deep feature decomposition and class-level alignment
Jingchuan Dong, Hongyu Jiang, Depeng Su, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 4, pp. 046006-046006
Closed Access | Times Cited: 8
Multiscale Channel Attention-Driven Graph Dynamic Fusion Learning Method for Robust Fault Diagnosis
Xin Zhang, Jie Liu, Xi Zhang, et al.
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 9, pp. 11002-11013
Closed Access | Times Cited: 8
Multi-view rotating machinery fault diagnosis with adaptive co-attention fusion network
Xiaorong Liu, Jie Wang, Sa Meng, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 122, pp. 106138-106138
Closed Access | Times Cited: 16
Hypergraph construction using Multi-Sensor for helicopter Tail-Drive system fault diagnosis
Aijun Yin, Zhaoyi Sun, Junlin Zhou
Measurement (2024) Vol. 231, pp. 114586-114586
Closed Access | Times Cited: 5
Temporal-Spatial Attention Network: A Novel Axial Piston Pump Coupled Fault Diagnosis Method
S. B. Liu, Junhui Zhang, Weidi Huang, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-15
Closed Access | Times Cited: 5
A federated learning based intelligent fault diagnosis framework for manufacturing processes with intraclass and interclass imbalance
Liang Ma, Fuzhong Shi, Kaixiang Peng
Measurement Science and Technology (2025) Vol. 36, Iss. 3, pp. 036203-036203
Closed Access
Multi-scale quadratic convolutional neural network for bearing fault diagnosis based on multi-sensor data fusion
Yingying Ji, Jun Gao, Xing Shao, et al.
Nonlinear Dynamics (2025)
Closed Access
An attention-enhanced multi-modal deep learning algorithm for robotic compound fault diagnosis
Xing Zhou, Hanlin Zeng, Chong Chen, et al.
Measurement Science and Technology (2022) Vol. 34, Iss. 1, pp. 014007-014007
Closed Access | Times Cited: 22
Intelligent fault diagnosis of rolling bearings based on the visibility algorithm and graph neural networks
Shaohui Ning, Yonglei Ren, Yukun Wu
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2023) Vol. 45, Iss. 2
Closed Access | Times Cited: 13
Fault detection in complex mechatronic systems by a hierarchical graph convolution attention network based on causal paths
Shuwen Zheng, Chong Wang, Enrico Zio, et al.
Reliability Engineering & System Safety (2023) Vol. 243, pp. 109872-109872
Closed Access | Times Cited: 13
Semi-supervised few-shot fault diagnosis driven by multi-head dynamic graph attention network under speed fluctuations
Li Jiang, Shuaiyu Wang, Tianao Zhang, et al.
Digital Signal Processing (2024) Vol. 151, pp. 104528-104528
Closed Access | Times Cited: 4
In-situ fault detection for the spindle motor of CNC machines via multi-stage residual fusion convolution neural networks
Yiming He, Hua Xiang, Hao Zhou, et al.
Computers in Industry (2022) Vol. 145, pp. 103810-103810
Closed Access | Times Cited: 20
A multisensory time-frequency features fusion method for rotating machinery fault diagnosis under nonstationary case
Jiayang Liu, Fuqi Xie, Qiang Zhang, et al.
Journal of Intelligent Manufacturing (2023) Vol. 35, Iss. 7, pp. 3197-3217
Closed Access | Times Cited: 10
An improved fault diagnosis method for rolling bearings based on wavelet packet decomposition and network parameter optimization
Fangyuan Zhao, Yulian Jiang, Chao Cheng, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 2, pp. 025004-025004
Closed Access | Times Cited: 9
A novel convolutional network with a self-adaptation high-pass filter for fault diagnosis of wind turbine gearboxes
Fan Yang, Donghua Huang, Dongdong Li, et al.
Measurement Science and Technology (2022) Vol. 34, Iss. 2, pp. 025024-025024
Closed Access | Times Cited: 13
Rolling bearing fault diagnosis based on multi-scale weighted visibility graph and multi-channel graph convolution network
Dong Guang Zuo, Tang Tang, Ming Chen
Measurement Science and Technology (2023) Vol. 34, Iss. 11, pp. 115019-115019
Closed Access | Times Cited: 7
Transfer Learning for Bearing Fault Diagnosis based on Graph Neural Network with Dilated KNN and Adversarial Discriminative Domain Adaptation
Tang Tang, Zeyuan Liu, Chuanhang Qiu, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 065106-065106
Closed Access | Times Cited: 2
Gearbox Fault Diagnosis Method Based on PSM-BN
Yuan Shanqin, Jinhua Wang, Jie Cao
IEEE Access (2024) Vol. 12, pp. 39876-39886
Open Access | Times Cited: 2
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