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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 under various operation conditions using synchrosqueezing transform and improved two-dimensional convolutional neural network
Lei Zhang, Yong Lv, Wenyi Huang, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 8, pp. 085002-085002
Closed Access | Times Cited: 25

Showing 25 citing articles:

An effective fault diagnosis approach for bearing using stacked de-noising auto-encoder with structure adaptive adjustment
Lerui Chen, Yidan Ma, Heyu Hu, et al.
Measurement (2023) Vol. 214, pp. 112774-112774
Closed Access | Times Cited: 36
A review on convolutional neural network in rolling bearing fault diagnosis
Xin Li, Zengqiang Ma, Zonghao Yuan, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 7, pp. 072002-072002
Closed Access | Times Cited: 9
Image deep learning in fault diagnosis of mechanical equipment
Chuanhao Wang, Yongjian Sun, Xiaohong Wang
Journal of Intelligent Manufacturing (2023) Vol. 35, Iss. 6, pp. 2475-2515
Closed Access | Times Cited: 13
Rotating Machinery Fault Diagnosis Under Multiple Working Conditions via a Time-Series Transformer Enhanced by Convolutional Neural Network
Zhiqiang Lu, Longyang Liang, Jun Zhu, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-11
Closed Access | Times Cited: 13
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: 4
A fault diagnosis method for key transmission components of rotating machinery based on SAM-1DCNN-BiLSTM temporal and spatial feature extraction
Wenliao Du, Xutong Niu, Hongchao Wang, et al.
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science (2025)
Closed Access
Small sample fault diagnosis for wind turbine gearbox based on lightweight multiscale convolutional neural network
Yuan Wang, Junnian Wang, Pengcheng Tong
Measurement Science and Technology (2023) Vol. 34, Iss. 9, pp. 095111-095111
Closed Access | Times Cited: 8
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
Bearings fault diagnosis method based on MAM and deep separable dilated convolutional neural network
Chunli Lei, Jiashuo Shi, Shuzhen Ma, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 11, pp. 114001-114001
Closed Access | Times Cited: 7
A rolling bearing fault diagnosis method based on Markov transition field and multi-scale Runge-Kutta residual network
Simin Ding, Zhiyuan Rui, Chunli Lei, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 12, pp. 125150-125150
Closed Access | Times Cited: 7
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
Novel Meta-Learning for Few-Shot Bearing Fault Diagnosis Under Varying Working Conditions
Chuanhao Wang, Jigang Peng, Yongjian Sun
Engineering Research Express (2024) Vol. 6, Iss. 3, pp. 035239-035239
Closed Access | Times Cited: 2
Intelligent diagnosis method of bearing fault based on ICEEMDAN and Ghost-IRCNN
Xueyan Zou, Deqiang He, Zhenzhen Jin, et al.
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science (2022) Vol. 237, Iss. 13, pp. 3115-3130
Closed Access | Times Cited: 8
LAFICNN: A Novel Convolutional Adaptive Fusion Framework for Fault Diagnosis of Rotating Machinery
Tianzhuang Yu, Zhaohui Ren, Yongchao Zhang, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-9
Closed Access | Times Cited: 1
Integrating self-attention mechanisms in deep learning: A novel dual-head ensemble transformer with its application to bearing fault diagnosis
Qing Snyder, Qingtang Jiang, Erin E. Tripp
Signal Processing (2024) Vol. 227, pp. 109683-109683
Closed Access | Times Cited: 1
Bearing Fault Diagnosis for Time-Varying System Using Vibration–Speed Fusion Network Based on Self-Attention and Sparse Feature Extraction
Fulin Chi, Xinyu Yang, Siyu Shao, et al.
Machines (2022) Vol. 10, Iss. 10, pp. 948-948
Open Access | Times Cited: 7
Time-frequency enhanced characterization method based on asymmetric image reconstruction autoencoder
Ruiyu Han, Zhiwei Mao, Zhenjing Zhang, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 3, pp. 035107-035107
Closed Access | Times Cited: 2
Non-Uniformly Weighted Multisource Domain Adaptation Network For Fault Diagnosis Under Varying Working Conditions
Hongliang Zhang, Yuteng Zhang, Rui Wang, et al.
Neural Processing Letters (2024) Vol. 56, Iss. 2
Open Access
DEFR-net: A decompose-enhance fourier residual network for fault diagnosis of rotating machine with high noise immunity
Baigang Du, Fujiang Zhang, Jun Guo, et al.
Journal of Intelligent & Fuzzy Systems (2024), pp. 1-22
Closed Access
非平稳过程异常监测方法：综述与展望
Min Wang, Zhibin Feng, Dehao Wu, et al.
Scientia Sinica Informationis (2024) Vol. 54, Iss. 8, pp. 1807-1807
Open Access
A hybrid deep learning network for diagnosing multipoint faults in rolling bearings under variable operating conditions
Y. Huang, Changfeng Yan, Bin Liu, et al.
Journal of Mechanical Science and Technology (2024) Vol. 38, Iss. 11, pp. 5989-6003
Closed Access
A multi-layer feature fusion fault diagnosis method for train bearings under noise and variable load working conditions
Changfu He, Deqiang He, Zhenzhen Jin, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 2, pp. 025121-025121
Closed Access | Times Cited: 1
Cross working condition bearing fault diagnosis based on the combination of multimodal network and entropy conditional domain adversarial network
Yuanpeng Feng, Peng Liu, Yixian Du, et al.
Journal of Vibration and Control (2023) Vol. 30, Iss. 23-24, pp. 5375-5386
Closed Access | Times Cited: 1
Running State Monitoring of Induction Motors Based on KPCA_RBF and Stator Current Characteristics
Xiao Song, Yelin Hu, Bin Dai, et al.
IEEE Access (2023) Vol. 11, pp. 65468-65479
Open Access
Image Feature Enhancement and Its Application in Fault Diagnosis of Rotating Machinery: A Review
Wei Wang, Yongjian Sun
Journal of Artificial Intelligence Machine Learning and Data Science (2023) Vol. 1, Iss. 3, pp. 86-99
Open Access
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