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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:

Digital twin-driven intelligent assessment of gear surface degradation
Ke Feng, Jinchen Ji, Yongchao Zhang, et al.
Mechanical Systems and Signal Processing (2022) Vol. 186, pp. 109896-109896
Closed Access | Times Cited: 312

Showing 1-25 of 312 citing articles:

Physics-Informed Residual Network (PIResNet) for rolling element bearing fault diagnostics
Qing Ni, Jinchen Ji, Benjamin Halkon, et al.
Mechanical Systems and Signal Processing (2023) Vol. 200, pp. 110544-110544
Open Access | Times Cited: 173
Digital twin-driven partial domain adaptation network for intelligent fault diagnosis of rolling bearing
Yongchao Zhang, Jinchen Ji, Zhaohui Ren, et al.
Reliability Engineering & System Safety (2023) Vol. 234, pp. 109186-109186
Open Access | Times Cited: 167
CFCNN: A novel convolutional fusion framework for collaborative fault identification of rotating machinery
Yadong Xu, Ke Feng, Xiaoan Yan, et al.
Information Fusion (2023) Vol. 95, pp. 1-16
Closed Access | Times Cited: 98
A novel vibration-based prognostic scheme for gear health management in surface wear progression of the intelligent manufacturing system
Ke Feng, Jinchen Ji, Qing Ni, et al.
Wear (2023) Vol. 522, pp. 204697-204697
Closed Access | Times Cited: 95
Product envelope spectrum optimization-gram: An enhanced envelope analysis for rolling bearing fault diagnosis
Bingyan Chen, Weihua Zhang, James Xi Gu, et al.
Mechanical Systems and Signal Processing (2023) Vol. 193, pp. 110270-110270
Open Access | Times Cited: 78
Digital Twin Enabled Domain Adversarial Graph Networks for Bearing Fault Diagnosis
Ke Feng, Yadong Xu, Yulin Wang, et al.
IEEE Transactions on Industrial Cyber-Physical Systems (2023) Vol. 1, pp. 113-122
Open Access | Times Cited: 59
Modified Varying Index Coefficient Autoregression Model for Representation of the Nonstationary Vibration From a Planetary Gearbox
Yuejian Chen, Meng Rao, Ke Feng, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-12
Closed Access | Times Cited: 56
Feature extraction of multi-sensors for early bearing fault diagnosis using deep learning based on minimum unscented kalman filter
Haihong Tang, Yanmin Tang, Yuxiang Su, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 127, pp. 107138-107138
Closed Access | Times Cited: 53
Generalized open-set domain adaptation in mechanical fault diagnosis using multiple metric weighting learning network
Zhuyun Chen, Jingyan Xia, Jipu Li, et al.
Advanced Engineering Informatics (2023) Vol. 57, pp. 102033-102033
Closed Access | Times Cited: 50
A novel digital twin-driven approach based on physical-virtual data fusion for gearbox fault diagnosis
Jingyan Xia, Ruyi Huang, Zhuyun Chen, et al.
Reliability Engineering & System Safety (2023) Vol. 240, pp. 109542-109542
Closed Access | Times Cited: 50
Digital twin-assisted multiscale residual-self-attention feature fusion network for hypersonic flight vehicle fault diagnosis
Yutong Dong, Hongkai Jiang, Zhenghong Wu, et al.
Reliability Engineering & System Safety (2023) Vol. 235, pp. 109253-109253
Closed Access | Times Cited: 44
Machinery multi-sensor fault diagnosis based on adaptive multivariate feature mode decomposition and multi-attention fusion residual convolutional neural network
Xiaoan Yan, Wang‐Ji Yan, Yadong Xu, et al.
Mechanical Systems and Signal Processing (2023) Vol. 202, pp. 110664-110664
Closed Access | Times Cited: 42
The advance of digital twin for predictive maintenance: The role and function of machine learning
Chong Chen, Huibin Fu, Yu Zheng, et al.
Journal of Manufacturing Systems (2023) Vol. 71, pp. 581-594
Open Access | Times Cited: 42
Few-Shot GAN: Improving the Performance of Intelligent Fault Diagnosis in Severe Data Imbalance
Zhijun Ren, Yongsheng Zhu, Zheng Liu, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-14
Closed Access | Times Cited: 40
Digital twin-assisted imbalanced fault diagnosis framework using subdomain adaptive mechanism and margin-aware regularization
Shen Yan, Xiang Zhong, Haidong Shao, et al.
Reliability Engineering & System Safety (2023) Vol. 239, pp. 109522-109522
Open Access | Times Cited: 40
Dynamic normalization supervised contrastive network with multiscale compound attention mechanism for gearbox imbalanced fault diagnosis
Yutong Dong, Hongkai Jiang, Wenxin Jiang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108098-108098
Closed Access | Times Cited: 32
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
Multi-cavitation states diagnosis of the vortex pump using a combined DT-CWT-VMD and BO-LW-KNN based on motor current signals
Weitao Zeng, Peijian Zhou, Yanzhao Wu, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 19, pp. 30690-30705
Closed Access | Times Cited: 25
Physics-informed machine learning: A comprehensive review on applications in anomaly detection and condition monitoring
Yuandi Wu, Brett Sicard, S. Andrew Gadsden
Expert Systems with Applications (2024) Vol. 255, pp. 124678-124678
Open Access | Times Cited: 15
A digital twin methodology for vibration-based monitoring and prediction of gear wear
Ke Feng, Huili Xiao, Jinchuan Zhang, et al.
Wear (2025), pp. 205806-205806
Closed Access | Times Cited: 1
A novel gear fatigue monitoring indicator and its application to remaining useful life prediction for spur gear in intelligent manufacturing systems
Ke Feng, Jinchen Ji, Qing Ni
International Journal of Fatigue (2022) Vol. 168, pp. 107459-107459
Closed Access | Times Cited: 61
A CNN‐BiLSTM‐Bootstrap integrated method for remaining useful life prediction of rolling bearings
Junyu Guo, Jiang Wang, Zhiyuan Wang, et al.
Quality and Reliability Engineering International (2023) Vol. 39, Iss. 5, pp. 1796-1813
Closed Access | Times Cited: 35
A physics-informed feature weighting method for bearing fault diagnostics
Hao Lü, Venkat Pavan Nemani, Vahid Barzegar, et al.
Mechanical Systems and Signal Processing (2023) Vol. 191, pp. 110171-110171
Open Access | Times Cited: 34
IFD-MDCN: Multibranch denoising convolutional networks with improved flow direction strategy for intelligent fault diagnosis of rolling bearings under noisy conditions
Sheng Li, Jinchen Ji, Yadong Xu, et al.
Reliability Engineering & System Safety (2023) Vol. 237, pp. 109387-109387
Open Access | Times Cited: 33
Automated and Adaptive Ridge Extraction for Rotating Machinery Fault Detection
Yifan Li, Yaocheng Yang, Ke Feng, et al.
IEEE/ASME Transactions on Mechatronics (2023) Vol. 28, Iss. 5, pp. 2565-2575
Closed Access | Times Cited: 32
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