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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:

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: 45

Showing 1-25 of 45 citing articles:

An In-Depth Study of Vibration Sensors for Condition Monitoring
Ietezaz Ul Hassan, Krishna Panduru, J. L. Walsh
Sensors (2024) Vol. 24, Iss. 3, pp. 740-740
Open Access | Times Cited: 18
Explainable Predictive Maintenance of Rotating Machines Using LIME, SHAP, PDP, ICE
Shreyas Gawde, Shruti Patil, Satish Kumar, et al.
IEEE Access (2024) Vol. 12, pp. 29345-29361
Open Access | Times Cited: 13
Unsupervised feature selection using chronological fitting with Shapley Additive explanation (SHAP) for industrial time-series anomaly detection
Qixuan Li, Yangjian Ji, Mingrui Zhu, et al.
Applied Soft Computing (2024) Vol. 155, pp. 111426-111426
Closed Access | Times Cited: 8
Exploring Local Explanation of Practical Industrial AI Applications: A Systematic Literature Review
Thi-Thu-Huong Le, Aji Teguh Prihatno, Yustus Eko Oktian, et al.
Applied Sciences (2023) Vol. 13, Iss. 9, pp. 5809-5809
Open Access | Times Cited: 20
Deep Learning-Enhanced Small-Sample Bearing Fault Analysis Using Q-Transform and HOG Image Features in a GRU-XAI Framework
Vipul Dave, Himanshu Borade, Hitesh Agrawal, et al.
Machines (2024) Vol. 12, Iss. 6, pp. 373-373
Open Access | Times Cited: 6
Fault diagnosis of belt conveyor idlers based on gradient boosting decision tree
João Lucas Lobato Soares, Thiago B Costa, Lis Silva de Moura, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 132, Iss. 7-8, pp. 3479-3488
Closed Access | Times Cited: 5
Explainable AI in Manufacturing and Industrial Cyber–Physical Systems: A Survey
Sajad Moosavi, Maryam Farajzadeh-Zanjani, Roozbeh Razavi–Far, et al.
Electronics (2024) Vol. 13, Iss. 17, pp. 3497-3497
Open Access | Times Cited: 5
Fault diagnosis of a CNC Hobbing Cutter through Machine Learning using three axis vibration data
Nagesh Tambake, Bhagyesh Deshmukh, Sujit S. Pardeshi, et al.
Heliyon (2025) Vol. 11, Iss. 2, pp. e41637-e41637
Open Access
Analyzing fragmentation response of heterogeneous ring using the method of characteristics and machine learning techniques
Reza Abedi, Colin Furey, Farhad Pourkamali‐Anaraki, et al.
Computer Methods in Applied Mechanics and Engineering (2025) Vol. 436, pp. 117709-117709
Closed Access
Novel Fault Diagnosis Method for Rolling Bearing Based on Voiceprint Recognition With FasterNet‐CAM
Wang Puzhou, Lin Yanghui, Yejun Li, et al.
Quality and Reliability Engineering International (2025)
Closed Access
A Systematic Review on Advancement of Image Segmentation Techniques for Fault Detection Opportunities and Challenges
Md. Motiur Rahman, Saeka Rahman, Smriti Bhatt, et al.
Electronics (2025) Vol. 14, Iss. 5, pp. 974-974
Open Access
Explainable fault diagnosis method based on statistical features for gearboxes
Huakang Tang, Honglei Wang, Chengjiang Li
Engineering Applications of Artificial Intelligence (2025) Vol. 148, pp. 110503-110503
Closed Access
An ensemble deep learning approach for air quality estimation in Delhi, India
Anju S. Mohan, Lizy Abraham
Earth Science Informatics (2024) Vol. 17, Iss. 3, pp. 1923-1948
Open Access | Times Cited: 4
Toward Explainable Metrology 4.0: Utilizing Explainable AI to Predict the Pointwise Accuracy of Laser Scanning Devices in Industrial Manufacturing
Eleni Lavasa, Christos G. Chadoulos, Athanasios Siouras, et al.
(2024), pp. 479-501
Open Access | Times Cited: 3
A Neural-Symbolic Network for Interpretable Fault Diagnosis of Rolling Element Bearings Based on Temporal Logic
Ruoyao Tian, Meijie Cui, Gang Chen
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-14
Closed Access | Times Cited: 3
A review of artificial intelligence applications in wind turbine health monitoring
Abirami Sasinthiran, G. Sakthivel, Ramesh Ragala
International Journal of Sustainable Energy (2024) Vol. 43, Iss. 1
Open Access | Times Cited: 3
Review of Data Processing Methods Used in Predictive Maintenance for Next Generation Heavy Machinery
Ietezaz Ul Hassan, Krishna Panduru, J. L. Walsh
Data (2024) Vol. 9, Iss. 5, pp. 69-69
Open Access | Times Cited: 3
Cutting-Edge AI Approaches with MAS for PdM in Industry 4.0: Challenges and Future Directions
Shadia Yahya Baroud
Journal of Applied Data Sciences (2024) Vol. 5, Iss. 2, pp. 455-473
Open Access | Times Cited: 3
Condition Monitoring and Fault Diagnosis of Rotating Machinery Towards Intelligent Manufacturing: Review and Prospect
Hui Zhang, W Che, Youren Cao, et al.
Iranian Journal of Science and Technology Transactions of Mechanical Engineering (2024)
Closed Access | Times Cited: 3
Enhancing Reliability Through Interpretability: A Comprehensive Survey of Interpretable Intelligent Fault Diagnosis in Rotating Machinery
Gang Chen, Junlin Yuan, Yiyue Zhang, et al.
IEEE Access (2024) Vol. 12, pp. 103348-103379
Open Access | Times Cited: 3
On the Soundness of XAI in Prognostics and Health Management (PHM)
David Solís-Martín, Juan Galán-Páez, Joaquín Borrego‐Díaz
Information (2023) Vol. 14, Iss. 5, pp. 256-256
Open Access | Times Cited: 8
Faults explanation based on a machine learning model for predictive maintenance purposes
Jonathan Jeremie Randriarison, Lala Rajaoarisoa, Moamar Sayed‐Mouchaweh
(2023), pp. 01-06
Closed Access | Times Cited: 8
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
A Fault Detection System for Wiring Harness Manufacturing Using Artificial Intelligence
Jinwoo Song, Prashant Kumar, Y. Kim, et al.
Mathematics (2024) Vol. 12, Iss. 4, pp. 537-537
Open Access | Times Cited: 2
Revolutionizing defect recognition in hard metal industry through AI explainability, human-in-the-loop approaches and cognitive mechanisms
Thanasis Kotsiopoulos, Gerasimos Papakostas, Thanasis Vafeiadis, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124839-124839
Closed Access | Times Cited: 2
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