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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:

Eigen-spectrograms: An interpretable feature space for bearing fault diagnosis based on artificial intelligence and image processing
Eugenio Brusa, Cristiana Delprete, Luigi Gianpio Di Maggio
Mechanics of Advanced Materials and Structures (2022) Vol. 30, Iss. 22, pp. 4639-4651
Open Access | Times Cited: 9

Showing 9 citing articles:

Explainable AI for Machine Fault Diagnosis: Understanding Features’ Contribution in Machine Learning Models for Industrial Condition Monitoring
Eugenio Brusa, Luca Cibrario, Cristiana Delprete, et al.
Applied Sciences (2023) Vol. 13, Iss. 4, pp. 2038-2038
Open Access | Times Cited: 46
Study on frequency spectrum characteristics and attenuation law of buried PE pipeline leakage infrasound signal
Yongmei Hao, Anning Wang, Yujia Wu, et al.
Mechanics of Advanced Materials and Structures (2025), pp. 1-10
Closed Access | Times Cited: 1
Dynamic Multibody Modeling of Spherical Roller Bearings with Localized Defects for Large-Scale Rotating Machinery
Luca Giraudo, Luigi Gianpio Di Maggio, Lorenzo Giorio, et al.
Sensors (2025) Vol. 25, Iss. 8, pp. 2419-2419
Open Access
Intelligent Fault Diagnosis of Industrial Bearings Using Transfer Learning and CNNs Pre-Trained for Audio Classification
Luigi Gianpio Di Maggio
Sensors (2022) Vol. 23, Iss. 1, pp. 211-211
Open Access | Times Cited: 20
Zero-Shot Generative AI for Rotating Machinery Fault Diagnosis: Synthesizing Highly Realistic Training Data via Cycle-Consistent Adversarial Networks
Luigi Gianpio Di Maggio, Eugenio Brusa, Cristiana Delprete
Applied Sciences (2023) Vol. 13, Iss. 22, pp. 12458-12458
Open Access | Times Cited: 8
On the effectiveness of standards application to threshold setting in vibration condition monitoring in industrial machinery
Cristiana Delprete, Chiara Gastaldi
Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability (2024)
Closed Access | Times Cited: 2
A Big Data Application in Manufacturing Industry-Computer Vision to Detect Defects on Bearings
Perin Unal, Özlem Albayrak, Meerim Kubatova, et al.
2021 IEEE International Conference on Big Data (Big Data) (2022), pp. 6074-6083
Closed Access | Times Cited: 3
Experimental and Statistical Study on the Noise Generated by Surface Defects of Bearing Rolling Bodies
Raffaella Sesana, Maria Anna Bafaro, Irene Pessolano Filos, et al.
(2024), pp. 511-524
Closed Access
Enhancing Trustworthiness in AI-Based Prognostics: A Comprehensive Review of Explainable AI for PHM
Duc An Nguyen, Khanh T.P. Nguyen, Kamal Medjaher
Springer series in reliability engineering (2024), pp. 101-136
Closed Access
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