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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 transfer learning method for rolling bearing fault diagnosis based on linear superposition network
Chunran Huo, Quan Jiang, Yehu Shen, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 121, pp. 105970-105970
Closed Access | Times Cited: 49

Showing 26-50 of 49 citing articles:

A novel intelligent bearing fault diagnosis method based on image enhancement and improved convolutional neural network
Guocai Nie, Zhongwei Zhang, Zonghao Jiao, et al.
Measurement (2024), pp. 116148-116148
Closed Access | Times Cited: 3
Adaptive manifold partial domain adaptation for fault transfer diagnosis of rotating machinery
Yi Qin, Quan Qian, Zhengyi Wang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107082-107082
Closed Access | Times Cited: 7
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
Bi-level binary coded fully connected classifier based on residual network 50 with bottom and deep level features for bearing fault diagnosis
Linfei Yin, Zixuan Wang
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108342-108342
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
Multi-Perception Graph Convolution Transfer Network Bearing Fault Diagnosis Method
Xiaolei Pan, Hongxiao Chen, Dongdong Zhao, et al.
Applied Sciences (2024) Vol. 14, Iss. 11, pp. 4515-4515
Open Access | Times Cited: 1
Federated Transfer Fault Diagnosis Method Based on Variational Auto-Encoding with Few-Shot Learning
Yang Ge, Yong Ren
Mathematics (2024) Vol. 12, Iss. 13, pp. 2142-2142
Open Access | Times Cited: 1
Adaptive feature fusion and disturbance correction for accurate remaining useful life prediction of rolling bearings
Kai Guo, Jun Ma, Jiande Wu, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 138, pp. 109433-109433
Closed Access | Times Cited: 1
A three-stage bearing transfer fault diagnosis method for large domain shift scenarios
Kai Huang, Zhijun Ren, Linbo Zhu, et al.
Reliability Engineering & System Safety (2024) Vol. 254, pp. 110641-110641
Closed Access | Times Cited: 1
Intra-domain self generalization network for intelligent fault diagnosis of bearings under unseen working conditions
Kai Huang, Zhijun Ren, Linbo Zhu, et al.
Advanced Engineering Informatics (2024) Vol. 64, pp. 102997-102997
Closed Access | Times Cited: 1
Contrastive learning and dynamics embedding neural network for label-free interpretable machine fault diagnosis
Shilong Sun, Tengyi Peng, Yu Zhou, et al.
ISA Transactions (2023) Vol. 144, pp. 436-451
Closed Access | Times Cited: 2
Multiscale convolutional conditional domain adversarial network with channel attention for unsupervised bearing fault diagnosis
H Wang, Yibin Li, Mingshun Jiang, et al.
Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering (2024) Vol. 238, Iss. 6, pp. 1123-1134
Closed Access
Fault Feature Extraction Method of Rolling Bearing Based on IAFD and TKEO
Kai Guo, Jun Ma, Xin Xiong, et al.
Journal of Sensors (2024) Vol. 2024, pp. 1-13
Open Access
Deep Learning Based Approaches for Intelligent Industrial Machineryhealth Management & Fault Diagnosis in Resource-Constrainedenvironments
Ali Saeed Khan
(2024)
Closed Access
A few-shot based phase-batch multi-layer domain adaptation pattern recognition method
Yiming Li, Jiankang Wang, Guangxu Luo, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 7, pp. 076105-076105
Closed Access
Fault diagnosis of power equipment based on variational autoencoder and semi‐supervised learning
B.G. Ye, Feng Li, Linghao Zhang, et al.
Concurrency and Computation Practice and Experience (2024) Vol. 36, Iss. 20
Closed Access
A new indirect transfer fault diagnosis method based on feature separation
Chenhui Qian, Zhaojun Yang, Jialong He, et al.
Knowledge-Based Systems (2024) Vol. 300, pp. 112058-112058
Closed Access
Research on Rolling Bearing Fault Diagnosis Method Based on Simulation Source Domain to Experimental Target Domain with Improved Alternating Transfer Learning
Heng Wang, Peng Wang, Siyuan Wang, et al.
Research Square (Research Square) (2024)
Closed Access
Deep Domain Adaptation Approach Using an Improved Parallel Residual Network for Cross‐Domain Bearing Fault Diagnosis
Jeng-Jie Huang
Shock and Vibration (2024) Vol. 2024, Iss. 1
Open Access
Fault Diagnosis for Rolling Bearings Under Complex Working Conditions Based on Domain-Conditioned Adaptation
Xu Zhang, G. Gu
Machines (2024) Vol. 12, Iss. 11, pp. 787-787
Open Access
Fault diagnosis of rotating machinery using a signal processing technique and lightweight model based on mechanical structural characteristics
Maodong Niu, Shangjun Ma, Haifeng Zhu, et al.
Measurement (2024), pp. 116505-116505
Closed Access
Adversarial domain adaptation based on contrastive learning for bearings fault diagnosis
Xiaolei Pan, Hongxiao Chen, Wei Wang, et al.
Simulation Modelling Practice and Theory (2024), pp. 103058-103058
Closed Access
Semi-Supervised Contrastive Transfer Learning Network for Fault Diagnosis of Cross-Working Condition Rolling Bearings
Xingchi Lu, Quan Jiang, Zhengchang Su, et al.
(2024), pp. 1-6
Closed Access
Deep Learning based Approaches for Intelligent Industrial Machinery Health Management & Fault Diagnosis in Resource-Constrained Environments
Ali Saeed Khan, Muhammad Usman Akram, Muazzam Khan Khattak, et al.
Research Square (Research Square) (2024)
Open Access
Prototype space boundary alignment network for bearing continuous fault diagnosis under class-incremental scenarios
Zhenzhong He, Juanjuan Shi, Weiguo Huang, et al.
IEEE Sensors Journal (2024) Vol. 25, Iss. 1, pp. 1076-1085
Closed Access
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