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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:

Physics-based Gaussian process for the health monitoring for a rolling bearing
Seyed M.Mehdi Hassani.N, Xiaoning Jin, Jun Ni
Acta Astronautica (2018) Vol. 154, pp. 133-139
Closed Access | Times Cited: 25

Showing 25 citing articles:

Towards multi-model approaches to predictive maintenance: A systematic literature survey on diagnostics and prognostics
Juan José Montero-Jiménez, Sébastien Schwartz, Rob Vingerhoeds, et al.
Journal of Manufacturing Systems (2020) Vol. 56, pp. 539-557
Open Access | Times Cited: 188
Artificial Intelligence in manufacturing: State of the art, perspectives, and future directions
Robert X. Gao, Jörg Krüger, Marion Merklein, et al.
CIRP Annals (2024) Vol. 73, Iss. 2, pp. 723-749
Open Access | Times Cited: 14
A Double-Channel Hybrid Deep Neural Network Based on CNN and BiLSTM for Remaining Useful Life Prediction
Chengying Zhao, Xianzhen Huang, Yuxiong Li, et al.
Sensors (2020) Vol. 20, Iss. 24, pp. 7109-7109
Open Access | Times Cited: 94
Bearing degradation assessment and remaining useful life estimation based on Kullback-Leibler divergence and Gaussian processes regression
Prem Shankar Kumar, L. A. Kumaraswamidhas, S. K. Laha
Measurement (2021) Vol. 174, pp. 108948-108948
Closed Access | Times Cited: 66
Remaining useful life prediction of rolling bearing based on multi-head attention embedded Bi-LSTM network
Yizhe Shen, Baoping Tang, Biao Li, et al.
Measurement (2022) Vol. 202, pp. 111803-111803
Closed Access | Times Cited: 51
Integrating physics-informed recurrent Gaussian process regression into instance transfer for predicting tool wear in milling process
Biyao Qiang, Kaining Shi, Ning Liu, et al.
Journal of Manufacturing Systems (2023) Vol. 68, pp. 42-55
Closed Access | Times Cited: 32
Remaining useful life prediction using nonlinear multi-phase Wiener process and variational Bayesian approach
Wen‐Yi Lin, Yi Chai, Linchuan Fan, et al.
Reliability Engineering & System Safety (2023) Vol. 242, pp. 109800-109800
Closed Access | Times Cited: 15
Remaining useful life prediction based on multi-stage Wiener process and Bayesian information criterion
Shuangchuan Wang, Mingjun Liu, Zengshou Dong
Computers & Industrial Engineering (2024) Vol. 196, pp. 110496-110496
Closed Access | Times Cited: 4
Knowledge Driven Machine Learning Towards Interpretable Intelligent Prognostics and Health Management: Review and Case Study
Ruqiang Yan, Zheng Zhou, Zuogang Shang, et al.
Chinese Journal of Mechanical Engineering (2025) Vol. 38, Iss. 1
Open Access
Physics-informed Gaussian Process Probabilistic Modeling with Multi-source Data for Prognostics of Degradation Processes
Chen Jiang, Teng Zhong, Hyunhee Choi, et al.
Reliability Engineering & System Safety (2025), pp. 110893-110893
Closed Access
On integrating prior knowledge into Gaussian processes for prognostic health monitoring
Simon Pfingstl, Markus Zimmermann
Mechanical Systems and Signal Processing (2022) Vol. 171, pp. 108917-108917
Open Access | Times Cited: 21
An unsupervised approach for health index building and for similarity-based remaining useful life estimation
Sébastien Schwartz, Juan José Montero-Jiménez, Rob Vingerhoeds, et al.
Computers in Industry (2022) Vol. 141, pp. 103716-103716
Open Access | Times Cited: 21
A stacked ensemble method based on TCN and convolutional bi-directional GRU with multiple time windows for remaining useful life estimation
Jun Guo, Dapeng Li, Baigang Du
Applied Soft Computing (2023) Vol. 150, pp. 111071-111071
Closed Access | Times Cited: 11
Physics-informed Gaussian process for tool wear prediction
Kunpeng Zhu, Cheng-Yi Huang, Si Li, et al.
ISA Transactions (2023) Vol. 143, pp. 548-556
Closed Access | Times Cited: 10
An improved deep convolution neural network for predicting the remaining useful life of rolling bearings
Yiming Guo, Hui Zhang, Zhijie Xia, et al.
Journal of Intelligent & Fuzzy Systems (2021) Vol. 40, Iss. 3, pp. 5743-5751
Closed Access | Times Cited: 12
Tacholess skidding evaluation and fault feature enhancement base on a two-step speed estimation method for rolling bearings
Chang Yan, Jing Lin, Kaixuan Liang, et al.
Mechanical Systems and Signal Processing (2021) Vol. 162, pp. 108017-108017
Closed Access | Times Cited: 12
Operational Status Evaluation of Smart Electricity Meters Using Gaussian Process Regression With Optimized-ARD Kernel
Junfeng Duan, Qiu Tang, Jun Ma, et al.
IEEE Transactions on Industrial Informatics (2023) Vol. 20, Iss. 2, pp. 1272-1282
Closed Access | Times Cited: 4
Utilizing multiple inputs autoregressive models for bearing remaining useful life prediction
Junliang Wang, Qinghua Zhang, Guanhua Zhu, et al.
Engineering Research Express (2024) Vol. 6, Iss. 3, pp. 035425-035425
Open Access | Times Cited: 1
Remaining Useful Life Prediction of Nuclear Power Machinery Based on an Exponential Degradation Model
Gaojun Liu, Weijie Fan, Fenglei Li, et al.
Science and Technology of Nuclear Installations (2022) Vol. 2022, pp. 1-9
Open Access | Times Cited: 6
A condition‐based maintenance optimization method with oscillating uncertain degradation process
Shuyu Li, Meilin Wen, Tianpei Zu, et al.
Quality and Reliability Engineering International (2024)
Closed Access
Data-driven drift detection and diagnosis framework for predictive maintenance of heterogeneous production processes: Application to a multiple tapping process
Julien Chapelin, Alexandre Voisin, Bertrand Rose, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 139, pp. 109552-109552
Open Access
Multi-Model Predictive Maintenance: Overview and A Linear System Perspective
Uğur Yıldırım, Shahin Mammadov, Hüseyin Afşer
Çukurova Üniversitesi Mühendislik Fakültesi Dergisi (2024) Vol. 39, Iss. 4, pp. 1039-1052
Closed Access
Tool Condition Monitoring Using Deep Learning in Machining Process
Byeonghui Park, Yoonjae Lee, Chang‐Woo Lee
Journal of the Korean Society for Precision Engineering (2020) Vol. 37, Iss. 6, pp. 415-420
Closed Access | Times Cited: 2
Fault detection and diagnostics of complex dynamic systems using Gaussian Process Models - nuclear power plant case study
Bartosz Puchalski
(2023), pp. 286-291
Closed Access
An Intelligent Screening Algorithm for Machine Equipment Faults∗
Yi Yang, Peirong Wang, Fan Liu
International Conference on Frontiers of Electronics, Information and Computation Technologies (2021), pp. 1-6
Closed Access
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