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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:

Research on bearing fault diagnosis method based on transformer neural network
Zhuohong Yang, Jian Cen, Xi Liu, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 8, pp. 085111-085111
Closed Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

Bearing fault diagnosis method using the joint feature extraction of Transformer and ResNet
Shixi Hou, Ao Lian, Yundi Chu
Measurement Science and Technology (2023) Vol. 34, Iss. 7, pp. 075108-075108
Closed Access | Times Cited: 24
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: 24
A Mask Self-Supervised Learning-Based Transformer for Bearing Fault Diagnosis With Limited Labeled Samples
Jian Cen, Zhuohong Yang, Yinbo Wu, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 10, pp. 10359-10369
Closed Access | Times Cited: 19
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
A Novel Multisensor Fusion Transformer and Its Application Into Rotating Machinery Fault Diagnosis
Chaoyang Weng, Baochun Lu, Qian Gu, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-12
Closed Access | Times Cited: 17
Fault diagnosis of nuclear power plant sliding bearing-rotor systems using deep convolutional generative adversarial networks
Qi Li, Weiwei Zhang, Feiyu Chen, et al.
Nuclear Engineering and Technology (2024) Vol. 56, Iss. 8, pp. 2958-2973
Open Access | Times Cited: 5
Measurement and diagnostic system for detecting and classifying faults in the rotary hay tedder using multilayer perceptron neural networks
Arkadiusz Mystkowski, Adam Wolniakowski, Adam Idźkowski, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108513-108513
Closed Access | Times Cited: 5
Transformer-based intelligent fault diagnosis methods of mechanical equipment: A survey
Rongcai Wang, Enzhi Dong, Zhonghua Cheng, et al.
Open Physics (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 5
A gearbox fault diagnosis method based on Swin Transformer and Markov transform fields
Jiangran Liu, Rujiang Hao, Feiyue Deng, et al.
Engineering Research Express (2025) Vol. 7, Iss. 1, pp. 015225-015225
Closed Access
Mixmamba-fewshot: mamba and attention mixer-based method with few-shot learning for bearing fault diagnosis
Thanh N. Nguyen, Van Quang Nguyen, Gia-Bao Truong, et al.
Applied Intelligence (2025) Vol. 55, Iss. 6
Closed Access
Time–frequency Transformer with shifted windows for journal bearing-rotor systems fault diagnosis under multiple working conditions
Feiyu Chen, Xiaojing Wang, Yan Zhu, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 8, pp. 085121-085121
Closed Access | Times Cited: 12
A fine-tuning deep learning framework to palliate data distribution shift effects in rotary machine fault detection
Nima Rezazadeh, Donato Perfetto, Mario De Oliveira, et al.
Structural Health Monitoring (2024)
Closed Access | Times Cited: 4
Deep Learning in Industrial Machinery: A Critical Review of Bearing Fault Classification Methods
Attiq Ur Rehman, Weidong Jiao, Yonghua Jiang, et al.
Applied Soft Computing (2025), pp. 112785-112785
Closed Access
An Improved Ship Classification Method Based on YOLOv7 Model with Attention Mechanism
Jian Cen, Hao Feng, Xi Liu, et al.
Wireless Communications and Mobile Computing (2023) Vol. 2023, pp. 1-18
Open Access | Times Cited: 11
A Multi-scale Attention-Based Transfer Model for Cross-bearing Fault Diagnosis
Puda Li
International Journal of Computational Intelligence Systems (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 3
A hybrid fault diagnosis method for rolling bearings based on GGRU-1DCNN with AdaBN algorithm under multiple load conditions
Lirong Sun, Xiaomin Zhu, Jiannan Xiao, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 7, pp. 076201-076201
Closed Access | Times Cited: 3
Fault Diagnosis of the Dynamic Chemical Process Based on the Optimized CNN-LSTM Network
Honghua Chen, Jian Cen, Zhuohong Yang, et al.
ACS Omega (2022) Vol. 7, Iss. 38, pp. 34389-34400
Open Access | Times Cited: 17
Bearing Health State Detection Based on Informer and CNN + Swin Transformer
Chunyang Liu, Weiwei Zou, Zhilei Hu, et al.
Machines (2024) Vol. 12, Iss. 7, pp. 456-456
Open Access | Times Cited: 3
Rolling bearing fault diagnosis method based on MTF-MFACNN
Chunli Lei, Chengxiang Miao, Huiyuan Wan, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 3, pp. 035007-035007
Closed Access | Times Cited: 7
AHFormer: Hypergraph embedding coding transformer and adaptive aggregation network for intelligent fault diagnosis under noise interference
Fangyuan Lei, Ziwei Chen, Xiangmin Luo, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102518-102518
Closed Access | Times Cited: 2
A Novel Method for Fault Migration Diagnosis of Rolling Bearings Based on MSCVIT Model
Xiuyan Liu, Dengfa He, Deyang Guo, et al.
Electronics (2024) Vol. 13, Iss. 23, pp. 4726-4726
Open Access | Times Cited: 2
A deep convolutional neural network model with two-stream feature fusion and cross-load adaptive characteristics for fault diagnosis
Wujiu Pan, Haoyong Qu, Yinghao Sun, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 9, pp. 095102-095102
Closed Access | Times Cited: 6
An explainable deep learning approach for detection and isolation of sensor and machine faults in predictive maintenance paradigm
Aparna Sinha, Debanjan Das
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 015122-015122
Closed Access | Times Cited: 6
A novel vision transformer network for rolling bearing remaining useful life prediction
Aijun Hu, Yancheng Zhu, Suixian Liu, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 2, pp. 025106-025106
Closed Access | Times Cited: 5
A Lightweight Bearing Compound Fault Diagnosis Method With Gram Angle Field and Ghost-ResNet Model
Yingkui Gu, Ronghua Chen, Peng Huang, et al.
IEEE Transactions on Reliability (2023) Vol. 73, Iss. 4, pp. 1768-1781
Closed Access | Times Cited: 5
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