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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:

Machine learning based anomaly detection and classification of acoustic emission events for wear monitoring in sliding bearing systems
Florian König, Christopher Sous, Achraf Ouald Chaib, et al.
Tribology International (2020) Vol. 155, pp. 106811-106811
Closed Access | Times Cited: 103

Showing 1-25 of 103 citing articles:

The Use of Artificial Intelligence in Tribology—A Perspective
Andreas Rosenkranz, Max Marian, Francisco J. Profito, et al.
Lubricants (2020) Vol. 9, Iss. 1, pp. 2-2
Open Access | Times Cited: 118
Tribo-informatics approaches in tribology research: A review
Nian Yin, Zhiguo Xing, Ke He, et al.
Friction (2022) Vol. 11, Iss. 1, pp. 1-22
Open Access | Times Cited: 57
Machine-Learning-Based Methods for Acoustic Emission Testing: A Review
Giuseppe Ciaburro, Gino Iannace
Applied Sciences (2022) Vol. 12, Iss. 20, pp. 10476-10476
Open Access | Times Cited: 55
The Role of Machine Learning in Tribology: A Systematic Review
Uma Maheshwera Reddy Paturi, Sai Teja Palakurthy, N.S. Reddy
Archives of Computational Methods in Engineering (2022) Vol. 30, Iss. 2, pp. 1345-1397
Closed Access | Times Cited: 55
Developing a heterogeneous ensemble learning framework to evaluate Alkali-silica reaction damage in concrete using acoustic emission signals
Li Ai, Vafa Soltangharaei, Paul Ziehl
Mechanical Systems and Signal Processing (2022) Vol. 172, pp. 108981-108981
Open Access | Times Cited: 48
A CNN-based transfer learning method for leakage detection of pipeline under multiple working conditions with AE signals
Pengqian Liu, Changhang Xu, Jing Xie, et al.
Process Safety and Environmental Protection (2022) Vol. 170, pp. 1161-1172
Closed Access | Times Cited: 48
Predicting EHL film thickness parameters by machine learning approaches
Max Marian, Jonas Mursak, Marcel Bartz, et al.
Friction (2022) Vol. 11, Iss. 6, pp. 992-1013
Open Access | Times Cited: 40
A hybrid prototype selection-based deep learning approach for anomaly detection in industrial machines
Rodrigo de Paula Monteiro, Mariela Cerrada, Diego Cabrera, et al.
Expert Systems with Applications (2022) Vol. 204, pp. 117528-117528
Closed Access | Times Cited: 38
A transfer learning approach for acoustic emission zonal localization on steel plate-like structure using numerical simulation and unsupervised domain adaptation
Li Ai, Bin Zhang, Paul Ziehl
Mechanical Systems and Signal Processing (2023) Vol. 192, pp. 110216-110216
Open Access | Times Cited: 33
Machine learning-based prediction of friction torque and friction coefficient in statically loaded radial journal bearings
Hasan Baş, Yunus Emre Karabacak
Tribology International (2023) Vol. 186, pp. 108592-108592
Closed Access | Times Cited: 24
Cross-scale data-based damage identification of CFRP laminates using acoustic emission and deep learning
Yuhang Liu, Kai Huang, Zhenxin Wang, et al.
Engineering Fracture Mechanics (2023) Vol. 294, pp. 109724-109724
Closed Access | Times Cited: 23
Review of rotating machinery elements condition monitoring using acoustic emission signal
Pradeep Kundu
Expert Systems with Applications (2024) Vol. 252, pp. 124169-124169
Closed Access | Times Cited: 8
Application of Machine Learning (ML)-based multi-classifications to identify corrosion fatigue cracking phenomena in Naval steel weldments
Vivek Srivastava, B. N. Basu, N. Prabhu
Materials Today Communications (2024) Vol. 39, pp. 108591-108591
Closed Access | Times Cited: 7
Data-driven wear monitoring for sliding bearings using acoustic emission signals and long short-term memory neural networks
Florian König, Jonas Marheineke, Georg Jacobs, et al.
Wear (2021) Vol. 476, pp. 203616-203616
Closed Access | Times Cited: 42
Intelligent prediction of wear location and mechanism using image identification based on improved Faster R-CNN model
Miao Wang, Lei Yang, Zhibin Zhao, et al.
Tribology International (2022) Vol. 169, pp. 107466-107466
Closed Access | Times Cited: 33
High-speed train wheel set bearing fault diagnosis and prognostics: Fingerprint feature recognition method based on acoustic emission
Dongming Hou, Hongyuan Qi, Cuiping Wang, et al.
Mechanical Systems and Signal Processing (2022) Vol. 171, pp. 108947-108947
Closed Access | Times Cited: 33
Nonintrusive heat flux quantification using acoustic emissions during pool boiling
Christy Dunlap, Hari Pandey, Ethan Weems, et al.
Applied Thermal Engineering (2023) Vol. 228, pp. 120558-120558
Open Access | Times Cited: 20
AI techniques for evaluating misaligned journal bearing performance: An approach beyond the Sommerfeld number
Georgios N. Rossopoulos, Christos I. Papadopoulos
Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology (2024) Vol. 238, Iss. 6, pp. 733-743
Closed Access | Times Cited: 6
Swarm intelligence algorithms for optimising sliding wear of nanocomposites
Nikolaos A. Fountas, John D. Kechagias, Nikolaos M. Vaxevanidis
Tribology and Materials (2024) Vol. 3, Iss. 1, pp. 44-50
Open Access | Times Cited: 5
Scraper conveyor gearbox fault diagnosis based on multi-source heterogeneous data fusion
Long Feng, Zeyu Ding, Yibing Yin, et al.
Measurement (2025), pp. 116797-116797
Closed Access
Detection of particle contamination and lubrication outage in journal bearings in wind turbine gearboxes using surface acoustic wave measurements and machine learning
Thomas Decker, Georg Jacobs, Malte Raddatz, et al.
Forschung im Ingenieurwesen (2025) Vol. 89, Iss. 1
Open Access
Predicting the coefficient of friction in a sliding contact by applying machine learning to acoustic emission data
Robert Gutiérrez, Tianshi Fang, Robert Mainwaring, et al.
Friction (2024) Vol. 12, Iss. 6, pp. 1299-1321
Open Access | Times Cited: 4
Roping Prediction Versus Detection: Could Prediction Be Possible?
Lin Yang, Lei Chen, Difan Tang, et al.
Minerals (2025) Vol. 15, Iss. 2, pp. 110-110
Open Access
Mechanism-guided wear severity assessment of worn surfaces with multiple damages
Qinghua Wang, Shuo Wang, Luning Zhang, et al.
Wear (2025), pp. 205875-205875
Closed Access
Physics-informed neural networks for the Reynolds equation with cavitation modeling
Michael Rom
Tribology International (2022) Vol. 179, pp. 108141-108141
Closed Access | Times Cited: 21
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