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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:

New transfer learning fault diagnosis method of rolling bearing based on ADC-CNN and LATL under variable conditions
Chunran Huo, Quan Jiang, Yehu Shen, et al.
Measurement (2021) Vol. 188, pp. 110587-110587
Closed Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

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: 48
Deep transfer learning strategy in intelligent fault diagnosis of rotating machinery
Shengnan Tang, Jingtao Ma, Zhengqi Yan, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108678-108678
Closed Access | Times Cited: 30
A novel intelligent diagnosis method of rolling bearing and rotor composite faults based on vibration signal-to-image mapping and CNN-SVM
Hongwei Fan, Ceyi Xue, Jiateng Ma, et al.
Measurement Science and Technology (2022) Vol. 34, Iss. 4, pp. 044008-044008
Closed Access | Times Cited: 43
Transfer learning based fault diagnosis of automobile dry clutch system
Ganjikunta Chakrapani, V. Sugumaran
Engineering Applications of Artificial Intelligence (2022) Vol. 117, pp. 105522-105522
Closed Access | Times Cited: 38
Intelligent Fault Diagnosis of Rolling Bearings Using Efficient and Lightweight ResNet Networks Based on an Attention Mechanism (September 2022)
Meng Chang, Dechen Yao, Jianwei Yang
IEEE Sensors Journal (2023) Vol. 23, Iss. 9, pp. 9136-9145
Closed Access | Times Cited: 27
Rolling Bearing Fault Diagnosis Method Based on Self-Calibrated Coordinate Attention Mechanism and Multi-Scale Convolutional Neural Network Under Small Samples
Linlin Xue, Chunli Lei, Mengxuan Jiao, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 9, pp. 10206-10214
Closed Access | Times Cited: 27
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
Multi-scale and multi-layer perceptron hybrid method for bearings fault diagnosis
Suchao Xie, Yaxin Li, Hongchuang Tan, et al.
International Journal of Mechanical Sciences (2022) Vol. 235, pp. 107708-107708
Closed Access | Times Cited: 35
A novel hierarchical training architecture for Siamese Neural Network based fault diagnosis method under small sample
Juanru Zhao, Yuan Mei, Jin Cui, et al.
Measurement (2023) Vol. 215, pp. 112851-112851
Closed Access | Times Cited: 14
Stability factor prediction of multilayer slope using three-dimensional convolutional neural network based on digital twin and prior knowledge data
Mansheng Lin, Gongfa Chen, Bo Hu, et al.
Environmental Earth Sciences (2024) Vol. 83, Iss. 8
Closed Access | Times Cited: 4
Multi‐Channel Deep Pulse‐Coupled Net: A Novel Bearing Fault Diagnosis Framework
Yanxi Wu, Yalin Yang, Zhuoran Yang, et al.
IET Image Processing (2025) Vol. 19, Iss. 1
Open Access
Enhanced rolling bearing fault diagnosis using a multi-stage attention fusion network
Mengling Ma, Chenxi Qu, Xüna Zhao, et al.
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science (2025)
Closed Access
Diesel Engine Fault Diagnosis Method Based on Optimized VMD and Improved CNN
Xianbiao Zhan, Huajun Bai, Hao Yan, et al.
Processes (2022) Vol. 10, Iss. 11, pp. 2162-2162
Open Access | Times Cited: 20
T-type inverter fault diagnosis based on GASF and improved AlexNet
Yabo Cui, Rongjie Wang, Yupeng Si, et al.
Energy Reports (2023) Vol. 9, pp. 2718-2731
Open Access | Times Cited: 9
Intelligent fault diagnosis method of rolling bearing based on multi-source domain fast adversarial network
Daoming She, Hongfei Zhang, Wang Hu, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 5, pp. 056119-056119
Closed Access | Times Cited: 3
An ensemble Swin-LE model with residuals for rolling bearing fault diagnosis
Xiaoyi Zhang, Lijun Li, Hui Shi, et al.
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2024) Vol. 46, Iss. 4
Closed Access | Times Cited: 3
Innovative integration of multi-scale residual networks and MK-MMD for enhanced feature representation in fault diagnosis
Xueyi Li, Peng Yuan, Kaiyu Su, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 8, pp. 086108-086108
Closed Access | Times Cited: 3
A multi-order moment matching-based unsupervised domain adaptation with application to cross-working condition fault diagnosis of rolling bearings
Qi Chang, Congcong Fang, Wei Zhou, et al.
Structural Health Monitoring (2024)
Closed Access | Times Cited: 3
Corn Harvester Bearing Fault Diagnosis Based on ABC-VMD and Optimized EfficientNet
Zhiyuan Liu, Wenlei Sun, Saike Chang, et al.
Entropy (2023) Vol. 25, Iss. 9, pp. 1273-1273
Open Access | Times Cited: 8
Fault diagnosis method for rolling bearing based on VMD and improved SVM optimized by METLBO
Chao Tan, Long Yang, Hao Chen, et al.
Journal of Mechanical Science and Technology (2022) Vol. 36, Iss. 10, pp. 4979-4991
Closed Access | Times Cited: 12
Few-shot condition diagnosis of rolling bearing using adversarial transfer network with class aggregation-guided
Shaoning Tian, Dong Zhen, Guohua Sun, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 066120-066120
Closed Access | Times Cited: 2
Image Enhancement Based on Dual-Branch Generative Adversarial Network Combining Spatial and Frequency Domain Information for Imbalanced Fault Diagnosis of Rolling Bearing
Yuguang Huang, Bin Wen, Weiqing Liao, et al.
Symmetry (2024) Vol. 16, Iss. 5, pp. 512-512
Open Access | Times Cited: 2
A Smart CEEMDAN, Bessel Transform and CNN-Based Scheme for Compound Gear-Bearing Fault Diagnosis
A. Andrews, Manisekar Kondal
Journal of Vibration Engineering & Technologies (2024)
Closed Access | Times Cited: 2
Rolling bearing fault diagnosis method based on dynamic simulated model from source domain to target domain with improved alternating transfer learning
Heng Wang, Peng Wang, Siyuan Wang, et al.
Nonlinear Dynamics (2024)
Closed Access | Times Cited: 2
Generalized Transfer Extreme Learning Machine for Unsupervised Cross-Domain Fault Diagnosis With Small and Imbalanced Samples
Aisong Qin, Hanling Mao, Jiankang Zhong, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 14, pp. 15831-15843
Closed Access | Times Cited: 5
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