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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:

Enhanced Lightweight Multiscale Convolutional Neural Network for Rolling Bearing Fault Diagnosis
Yaowei Shi, Aidong Deng, Minqiang Deng, et al.
IEEE Access (2020) Vol. 8, pp. 217723-217734
Open Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

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: 311
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: 150
A Review of Data-Driven Machinery Fault Diagnosis Using Machine Learning Algorithms
Jian Cen, Zhuohong Yang, Xi Liu, et al.
Journal of Vibration Engineering & Technologies (2022) Vol. 10, Iss. 7, pp. 2481-2507
Closed Access | Times Cited: 88
Multisource domain factorization network for cross-domain fault diagnosis of rotating machinery: An unsupervised multisource domain adaptation method
Yaowei Shi, Aidong Deng, Xue Ding, et al.
Mechanical Systems and Signal Processing (2021) Vol. 164, pp. 108219-108219
Closed Access | Times Cited: 58
Rolling Bearing Compound Fault Diagnosis Based on Parameter Optimization MCKD and Convolutional Neural Network
Shuzhi Gao, Shuo Shi, Yimin Zhang
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-8
Closed Access | Times Cited: 53
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
Lightweight Multiscale Convolutional Networks With Adaptive Pruning for Intelligent Fault Diagnosis of Train Bogie Bearings in Edge Computing Scenarios
Ao Ding, Yong Qin, Biao Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 72, pp. 1-13
Closed Access | Times Cited: 40
Rolling bearing fault diagnosis method based on DSICNN under strong noise background
Chunli Lei, Lu Wang, Qiyue Zhang, et al.
Nondestructive Testing And Evaluation (2025), pp. 1-17
Closed Access | Times Cited: 1
Digital twin-driven focal modulation-based convolutional network for intelligent fault diagnosis
Sheng Li, Qiubo Jiang, Yadong Xu, et al.
Reliability Engineering & System Safety (2023) Vol. 240, pp. 109590-109590
Closed Access | Times Cited: 18
A lightweight transformer based on feature fusion and global-local parallel stacked self-activation unit for bearing fault diagnosis
Yandong Hou, Tianzhi Li, Jinjin Wang, et al.
Measurement (2024) Vol. 236, pp. 115068-115068
Closed Access | Times Cited: 6
Scnet: spectral convolutional networks for multivariate time series classification
Xing Wu, Xinyu Xing, Junfeng Yao, et al.
Applied Intelligence (2025) Vol. 55, Iss. 6
Open Access
Fault detection and classification in kinematic chains by means of PCA extraction-reduction of features from thermographic images
Roque A. Osornio‐Rios, Arturo Yosimar Jaen-Cuéllar, Alvaro Ivan Alvarado-Hernandez, et al.
Measurement (2022) Vol. 197, pp. 111340-111340
Open Access | Times Cited: 20
Identifying Bearing Faults Using Multiscale Residual Attention and Multichannel Neural Network
Chun‐Yao Lee, Guang‐Lin Zhuo
IEEE Access (2023) Vol. 11, pp. 26953-26963
Open Access | Times Cited: 11
DPCCNN: A new lightweight fault diagnosis model for small samples and high noise problem
Jiabin Zhang, Zhiqian Zhao, Yinghou Jiao, et al.
Neurocomputing (2025), pp. 129526-129526
Closed Access
An Explainable and Lightweight Improved 1-D CNN Model for Vibration Signals of Rotating Machinery
Pengfei Pang, Jian Tang, Jiqing Luo, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 5, pp. 6976-6997
Open Access | Times Cited: 3
Multisensor Fusion Time–Frequency Analysis of Thruster Blade Fault Diagnosis Based on Deep Learning
Chia-Ming Tsai, Chiao-Sheng Wang, Yu-Jen Chung, et al.
IEEE Sensors Journal (2022) Vol. 22, Iss. 20, pp. 19761-19771
Closed Access | Times Cited: 15
A deep feature extraction approach for bearing fault diagnosis based on multi-scale convolutional autoencoder and generative adversarial networks
Zhiyong Hu, T. T. Han, Jun Bian, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 6, pp. 065013-065013
Closed Access | Times Cited: 14
Rolling bearing fault diagnosis under time-varying speeds based on time-characteristic order spectrum and multi-scale domain adaptation network
Zhenli Xu, Guiji Tang, Bin Pang, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 12, pp. 125118-125118
Closed Access | Times Cited: 7
A rolling bearing fault diagnosis method based on a convolutional neural network with frequency attention mechanism
Hui Zhou, Runda Liu, Yaxin Li, et al.
Structural Health Monitoring (2023) Vol. 23, Iss. 4, pp. 2475-2495
Open Access | Times Cited: 7
A Method for Constructing Automatic Rolling Bearing Fault Identification Model Based on Refined Composite Multi-Scale Dispersion Entropy
Qingfeng Wang, Yang Xiao, Shuai Wang, et al.
IEEE Access (2021) Vol. 9, pp. 86412-86428
Open Access | Times Cited: 13
Joint Threshold Learning Convolutional Networks for Intelligent Fault Diagnosis Under Nonstationary Conditions
Sheng Li, Yadong Xu, Ke Feng, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-11
Closed Access | Times Cited: 5
A novel multiscale feature adversarial fusion network for unsupervised cross-domain fault diagnosis
Yaowei Shi, Aidong Deng, Minqiang Deng, et al.
Measurement (2022) Vol. 200, pp. 111616-111616
Closed Access | Times Cited: 8
Machine Fault Diagnosis Method Using Lightweight 1-D Separable Convolution and WSNs With Sensor Computing
Liqun Hou, Lan Liu, Guopeng Mao
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-8
Closed Access | Times Cited: 8
An improved multi-scale branching convolutional neural network for rolling bearing fault diagnosis
Meng Xu, Yaowei Shi, Minqiang Deng, et al.
PLoS ONE (2023) Vol. 18, Iss. 9, pp. e0291353-e0291353
Open Access | Times Cited: 4
Shuffle-fusion pyramid network for bearing fault diagnosis under noisy environments
Cheng Zhao, Linfeng Deng, Yuanwen Zhang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 11, pp. 116133-116133
Closed Access | Times Cited: 1
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