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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:

The emerging graph neural networks for intelligent fault diagnostics and prognostics: A guideline and a benchmark study
Tianfu Li, Zheng Zhou, Sinan Li, et al.
Mechanical Systems and Signal Processing (2021) Vol. 168, pp. 108653-108653
Closed Access | Times Cited: 321

Showing 1-25 of 321 citing articles:

FGDAE: A new machinery anomaly detection method towards complex operating conditions
Shen Yan, Haidong Shao, Zhishan Min, et al.
Reliability Engineering & System Safety (2023) Vol. 236, pp. 109319-109319
Open Access | Times Cited: 117
LiConvFormer: A lightweight fault diagnosis framework using separable multiscale convolution and broadcast self-attention
Shen Yan, Haidong Shao, Jie Wang, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121338-121338
Open Access | Times Cited: 100
A review on deep learning in planetary gearbox health state recognition: methods, applications, and dataset publication
Dongdong Liu, Lingli Cui, Weidong Cheng
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 012002-012002
Closed Access | Times Cited: 90
Convformer-NSE: A Novel End-to-End Gearbox Fault Diagnosis Framework Under Heavy Noise Using Joint Global and Local Information
Song-Yu Han, Haidong Shao, Junsheng Cheng, et al.
IEEE/ASME Transactions on Mechatronics (2022) Vol. 28, Iss. 1, pp. 340-349
Closed Access | Times Cited: 80
A gated graph convolutional network with multi-sensor signals for remaining useful life prediction
Lei Wang, Hongrui Cao, Hao Xu, et al.
Knowledge-Based Systems (2022) Vol. 252, pp. 109340-109340
Closed Access | Times Cited: 77
Spatio-Temporal Fusion Attention: A Novel Approach for Remaining Useful Life Prediction Based on Graph Neural Network
Ziqian Kong, Xiaohang Jin, Zhengguo Xu, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-12
Closed Access | Times Cited: 77
Spatial graph convolutional neural network via structured subdomain adaptation and domain adversarial learning for bearing fault diagnosis
Mohammadreza Ghorvei, Mohammadreza Kavianpour, Mohammad Taghi Hamidi Beheshti, et al.
Neurocomputing (2022) Vol. 517, pp. 44-61
Open Access | Times Cited: 77
Deep Learning Techniques in Intelligent Fault Diagnosis and Prognosis for Industrial Systems: A Review
Shaohua Qiu, Xiaopeng Cui, Zuowei Ping, et al.
Sensors (2023) Vol. 23, Iss. 3, pp. 1305-1305
Open Access | Times Cited: 70
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: 69
Rotating Machinery Fault Diagnosis Under Time-Varying Speeds: A Review
Dongdong Liu, Lingli Cui, Huaqing Wang
IEEE Sensors Journal (2023) Vol. 23, Iss. 24, pp. 29969-29990
Open Access | Times Cited: 60
A novel digital twin-driven approach based on physical-virtual data fusion for gearbox fault diagnosis
Jingyan Xia, Ruyi Huang, Zhuyun Chen, et al.
Reliability Engineering & System Safety (2023) Vol. 240, pp. 109542-109542
Closed Access | Times Cited: 52
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: 49
Digital twin-driven graph domain adaptation neural network for remaining useful life prediction of rolling bearing
Lingli Cui, Yongchang Xiao, Dongdong Liu, et al.
Reliability Engineering & System Safety (2024) Vol. 245, pp. 109991-109991
Closed Access | Times Cited: 49
Trend-augmented and temporal-featured Transformer network with multi-sensor signals for remaining useful life prediction
Yuru Zhang, Chun Su, Jiajun Wu, et al.
Reliability Engineering & System Safety (2023) Vol. 241, pp. 109662-109662
Closed Access | Times Cited: 47
Condition monitoring of wind turbines with the implementation of spatio-temporal graph neural network
Jiayang Liu, Xiaosun Wang, Fuqi Xie, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 121, pp. 106000-106000
Closed Access | Times Cited: 45
Digital twin-assisted imbalanced fault diagnosis framework using subdomain adaptive mechanism and margin-aware regularization
Shen Yan, Xiang Zhong, Haidong Shao, et al.
Reliability Engineering & System Safety (2023) Vol. 239, pp. 109522-109522
Open Access | Times Cited: 44
Single and simultaneous fault diagnosis of gearbox via wavelet transform and improved deep residual network under imbalanced data
Suiyan Wang, Jiaye Tian, Pengfei Liang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108146-108146
Closed Access | Times Cited: 43
Multi-sensor fusion fault diagnosis method of wind turbine bearing based on adaptive convergent viewable neural networks
Xinming Li, Yanxue Wang, Jiachi Yao, et al.
Reliability Engineering & System Safety (2024) Vol. 245, pp. 109980-109980
Closed Access | Times Cited: 37
Dynamic normalization supervised contrastive network with multiscale compound attention mechanism for gearbox imbalanced fault diagnosis
Yutong Dong, Hongkai Jiang, Wenxin Jiang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108098-108098
Closed Access | Times Cited: 34
Temporal multi-resolution hypergraph attention network for remaining useful life prediction of rolling bearings
Jinxin Wu, Deqiang He, Jiayi Li, et al.
Reliability Engineering & System Safety (2024) Vol. 247, pp. 110143-110143
Closed Access | Times Cited: 34
PSparseFormer: Enhancing Fault Feature Extraction Based on Parallel Sparse Self-Attention and Multiscale Broadcast Feedforward Block
Jie Wang, Haidong Shao, Ying Peng, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 13, pp. 22982-22991
Closed Access | Times Cited: 28
Deep dynamic high-order graph convolutional network for wear fault diagnosis of hydrodynamic mechanical seal
Xinglin Li, Luofeng Xie, Bo Deng, et al.
Reliability Engineering & System Safety (2024) Vol. 247, pp. 110117-110117
Closed Access | Times Cited: 25
Graph structure few-shot prognostics for machinery remaining useful life prediction under variable operating conditions
Peng Ding, Jun Xia, Xiaoli Zhao, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102360-102360
Closed Access | Times Cited: 16
Multi-perception Graph Convolutional Tree-embedded Network for Aero-engine Bearing Health Monitoring with Unbalanced Data
Dezun Zhao, Wenbin Cai, Lingli Cui
Reliability Engineering & System Safety (2025) Vol. 257, pp. 110888-110888
Closed Access | Times Cited: 5
Multi-scale dynamic graph mutual information network for planet bearing health monitoring under imbalanced data
Wenbin Cai, Dezun Zhao, Tianyang Wang
Advanced Engineering Informatics (2025) Vol. 64, pp. 103096-103096
Closed Access | Times Cited: 4
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