Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

An anti-noise one-dimension convolutional neural network learning model applying on bearing fault diagnosis
Fengqian Zou, Haifeng Zhang, Shengtian Sang, et al.
Measurement (2021) Vol. 186, pp. 110236-110236
Closed Access | Times Cited: 54

Showing 1-25 of 54 citing articles:

A novel LSTM-autoencoder and enhanced transformer-based detection method for shield machine cutterhead clogging
Chengjin Qin, Ruihong Wu, Guoqiang Huang, et al.
Science China Technological Sciences (2023) Vol. 66, Iss. 2, pp. 512-527
Closed Access | Times Cited: 57
An intelligent bearing fault diagnosis framework: one-dimensional improved self-attention-enhanced CNN and empirical wavelet transform
Zhilin Dong, Dezun Zhao, Lingli Cui
Nonlinear Dynamics (2024) Vol. 112, Iss. 8, pp. 6439-6459
Open Access | Times Cited: 35
Insights into modern machine learning approaches for bearing fault classification: A systematic literature review
Afzal Ahmed Soomro, Masdi Muhammad, Ainul Akmar Mokhtar, et al.
Results in Engineering (2024) Vol. 23, pp. 102700-102700
Open Access | Times Cited: 18
A multi-scale convolutional neural network for bearing compound fault diagnosis under various noise conditions
Yanrui Jin, Chengjin Qin, ZhiNan Zhang, et al.
Science China Technological Sciences (2022) Vol. 65, Iss. 11, pp. 2551-2563
Closed Access | Times Cited: 44
Development of deep reinforcement learning-based fault diagnosis method for rotating machinery in nuclear power plants
Gensheng Qian, Jingquan Liu
Progress in Nuclear Energy (2022) Vol. 152, pp. 104401-104401
Closed Access | Times Cited: 40
Triplet attention-enhanced residual tree-inspired decision network: A hierarchical fault diagnosis model for unbalanced bearing datasets
Lingli Cui, Zhilin Dong, Hai Xu, et al.
Advanced Engineering Informatics (2023) Vol. 59, pp. 102322-102322
Closed Access | Times Cited: 32
MIFDELN: A multi-sensor information fusion deep ensemble learning network for diagnosing bearing faults in noisy scenarios
Maoyou Ye, Xiaoan Yan, Dong Jiang, et al.
Knowledge-Based Systems (2023) Vol. 284, pp. 111294-111294
Closed Access | Times Cited: 28
A novel rolling bearing fault diagnosis method based on Adaptive Denoising Convolutional Neural Network under noise background
Qiang Wang, Feiyun Xu
Measurement (2023) Vol. 218, pp. 113209-113209
Closed Access | Times Cited: 21
ISEANet: An interpretable subdomain enhanced adaptive network for unsupervised cross-domain fault diagnosis of rolling bearing
Bin Liu, Changfeng Yan, Yaofeng Liu, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102610-102610
Closed Access | Times Cited: 10
Fault Diagnosis Method and Application Based on Multi-scale Neural Network and Data Enhancement for Strong Noise
Zhehui Shao, Wenqiang Li, Hai Xiang, et al.
Journal of Vibration Engineering & Technologies (2023) Vol. 12, Iss. 1, pp. 295-308
Closed Access | Times Cited: 19
A gray texture image data-driven intelligent fault diagnosis method of induction motor rotor-bearing system under variable load conditions
Hongwei Fan, Zhongfu Ren, Xuhui Zhang, et al.
Measurement (2024) Vol. 233, pp. 114742-114742
Closed Access | Times Cited: 7
Deep Residual Multiscale Convolutional Neural Network With Attention Mechanism for Bearing Fault Diagnosis Under Strong Noise Environment
Shuzhen Han, Shengke Sun, Zhanshan Zhao, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 6, pp. 9073-9081
Closed Access | Times Cited: 5
TSoft-Net: A novel transfer soft thresholding network based on self-attention for intelligent fault diagnosis of rotating machinery
Shihang Yu, Shanchen Pang, Limei Song, et al.
Measurement (2024) Vol. 227, pp. 114237-114237
Closed Access | Times Cited: 5
An FPGA-Based SiNW-FET Biosensing System for Real-Time Viral Detection: Hardware Amplification and 1D CNN for Adaptive Noise Reduction
Ahmed Hadded, Mossaad Ben Ayed, Shaya A. Alshaya
Sensors (2025) Vol. 25, Iss. 1, pp. 236-236
Open Access
A multi-branch attention coupled convolutional domain adaptation network for bearing intelligent fault recognition under unlabeled sample scenarios
Maoyou Ye, Xiaoan Yan, Dong Jiang, et al.
Applied Soft Computing (2025), pp. 113053-113053
Closed Access
Noise-robust machinery fault diagnosis based on self-attention mechanism in wavelet domain
Aosheng Tian, Ye Zhang, Chao Ma, et al.
Measurement (2022) Vol. 207, pp. 112327-112327
Closed Access | Times Cited: 25
An Adaptive Multisensor Fault Diagnosis Method for High-Speed Train Bogie
Jie Man, Honghui Dong, Limin Jia, et al.
IEEE Transactions on Intelligent Transportation Systems (2023) Vol. 24, Iss. 6, pp. 6292-6306
Closed Access | Times Cited: 15
A Deep Convolution Multi-Adversarial adaptation network with Correlation Alignment for fault diagnosis of rotating machinery under different working conditions
Li Jiang, Lei Wei, Shuaiyu Wang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107179-107179
Closed Access | Times Cited: 14
Rolling Bearing Fault Diagnosis Based on 2D CNN and Hybrid Kernel Fuzzy SVM
Qingbao Zhang, Zhe Ju
Advanced Theory and Simulations (2025)
Closed Access
Intelligent chatter detection in high-speed milling using successive variational mode decomposition and a multi-channel feature fusion network
Liangshi Sun, Xianzhen Huang, Jiatong Zhao, et al.
Computers in Industry (2025) Vol. 167, pp. 104266-104266
Closed Access
A robust multi-scale learning network with quasi-hyperbolic momentum-based Adam optimizer for bearing intelligent fault diagnosis under sample imbalance scenarios and strong noise environment
Maoyou Ye, Xiaoan Yan, Ning Chen, et al.
Structural Health Monitoring (2023) Vol. 23, Iss. 3, pp. 1664-1686
Closed Access | Times Cited: 12
Deep transfer learning rolling bearing fault diagnosis method based on convolutional neural network feature fusion
Di Yu, H.C. Fu, Yanchen Song, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 015013-015013
Closed Access | Times Cited: 12
Gearbox fault diagnosis based on temporal shrinkage interpretable deep reinforcement learning under strong noise
Zeqi Wei, Hui Wang, Zhibin Zhao, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 139, pp. 109644-109644
Closed Access | Times Cited: 3
A new detection method for the ageing state of composite insulators based on spectral–spatial feature fusion
Yang Liu, Yujun Guo, Guangning Wu, et al.
Expert Systems with Applications (2024) Vol. 254, pp. 124353-124353
Closed Access | Times Cited: 3
A multistage model for rapid identification of geological features in shield tunnelling
Min Hu, Jing Lu, Wenbo Zhou, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 8
Page 1 - Next Page

Scroll to top