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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:

Fleet-based early fault detection of wind turbine gearboxes using physics-informed deep learning based on cyclic spectral coherence
Fabian Perez-Sanjines, Cédric Peeters, Timothy Verstraeten, et al.
Mechanical Systems and Signal Processing (2022) Vol. 185, pp. 109760-109760
Open Access | Times Cited: 36

Showing 26-50 of 36 citing articles:

Wind Turbine Anomaly Detection and Identification based on Graph Neural Networks with Decision Interpretability
Guoqian Jiang, Zichen Yi, Qun He
Measurement Science and Technology (2024) Vol. 35, Iss. 11, pp. 116141-116141
Closed Access | Times Cited: 1
Nonlinear characterization of enhanced and generalized Hjorth’s feature space for bearing condition monitoring
Wei Li, Yi Wang, Feng Lv, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 015128-015128
Open Access | Times Cited: 2
Symmetric circulant matrix decomposition-based multivariable group sparse coding for rolling bearing fault diagnosis
Xing Yuan, Hui Liu, Yang Fu, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 065017-065017
Open Access
Offshore field experimentation for novel hybrid condition monitoring approaches
Kayacan Kestel, Faras Jamil, Jens Jo Matthys, et al.
Journal of Physics Conference Series (2024) Vol. 2745, Iss. 1, pp. 012009-012009
Open Access
Machine Learning and Cointegration for Wind Turbine Monitoring and Fault Detection: From a Comparative Study to a Combined Approach
Paweł Knes, Phong B. Dao
Energies (2024) Vol. 17, Iss. 20, pp. 5055-5055
Open Access
Optimal Modeling of Deep Groove Ball Bearings for Application in Multibody Dynamics Simulations
Josef Koutsoupakis, Dimitrios Giagopoulos
Conference proceedings of the Society for Experimental Mechanics (2024), pp. 39-45
Closed Access
Investigation on morphological filtering via enhanced adaptive time-varying structural element for bearing fault diagnosis
Shengbo Wang, Bingyan Chen, Yao Cheng, et al.
Measurement (2024), pp. 116466-116466
Closed Access
Fatigue Crack Detection in Planetary Gears: Insights from the Hums2023 Data Challenge
Cédric Peeters, Wenyi Wang, David Blunt, et al.
(2023)
Closed Access | Times Cited: 1
Rolling bearing weak fault detection using transient structure‐optimal VMD and adaptive group sparse coding
Xing Yuan, Hui Liu, Huijie Zhang
IET Science Measurement & Technology (2023) Vol. 18, Iss. 2, pp. 86-102
Open Access | Times Cited: 1
Cyclicalnet: Modeling Temporal Dependencies with 2d Shifts for Exploring Underlying Patterns in Sequential Vibration Signals
Chaojun Xu, Peng Chen, Zheng Li, et al.
(2023)
Closed Access
Optimal Contact-Impact Force Model Selection for Damage Detection in Ball Bearings
Josef Koutsoupakis, Dimitrios Giagopoulos, Panagiotis Seventekidis
Conference proceedings of the Society for Experimental Mechanics (2023), pp. 121-127
Closed Access
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