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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:

Towards Developing an Automated Faults Characterisation Framework for Rotating Machines. Part 1: Rotor-Related Faults
Akilu Yunusa‐Kaltungo, Ruifeng Cao
Energies (2020) Vol. 13, Iss. 6, pp. 1394-1394
Open Access | Times Cited: 22

Showing 22 citing articles:

Intelligent algorithms and control strategies for battery management system in electric vehicles: Progress, challenges and future outlook
Molla Shahadat Hossain Lipu, M. A. Hannan, Tahia Fahrin Karim, et al.
Journal of Cleaner Production (2021) Vol. 292, pp. 126044-126044
Closed Access | Times Cited: 319
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: 17
A scoping review on multi-fault diagnosis of industrial rotating machines using multi-sensor data fusion
Shreyas Gawde, Shruti Patil, Satish Kumar, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 5, pp. 4711-4764
Closed Access | Times Cited: 43
Intelligent Fault Diagnosis of Hydraulic Piston Pump Based on Wavelet Analysis and Improved AlexNet
Yong Zhu, Guangpeng Li, Rui Wang, et al.
Sensors (2021) Vol. 21, Iss. 2, pp. 549-549
Open Access | Times Cited: 44
RUL Prediction of Rolling Bearings Based on a DCAE and CNN
Chenyang Wang, Wanlu Jiang, Xukang Yang, et al.
Applied Sciences (2021) Vol. 11, Iss. 23, pp. 11516-11516
Open Access | Times Cited: 43
Deep Learning Approach for Vibration Signals Applications
Han-Yun Chen, Ching‐Hung Lee
Sensors (2021) Vol. 21, Iss. 11, pp. 3929-3929
Open Access | Times Cited: 40
A whole-building data-driven fault detection and diagnosis approach for public buildings in hot climate regions
Ashraf Alghanmi, Akilu Yunusa‐Kaltungo
Energy and Built Environment (2023) Vol. 5, Iss. 6, pp. 911-932
Open Access | Times Cited: 9
An Automated Data Fusion-Based Gear Faults Classification Framework in Rotating Machines
Ruifeng Cao, Akilu Yunusa‐Kaltungo
Sensors (2021) Vol. 21, Iss. 9, pp. 2957-2957
Open Access | Times Cited: 20
Experimental Vibration Data in Fault Diagnosis: A Machine Learning Approach to Robust Classification of Rotor and Bearing Defects in Rotating Machines
Khalid M. Almutairi, Jyoti K. Sinha
Machines (2023) Vol. 11, Iss. 10, pp. 943-943
Open Access | Times Cited: 7
Transient behavior representation, contribution to fault current assessment, and transient response improvement in DFIG-based wind turbines assisted with crowbar hardware
Mohsen Rahimi, Ali Azizi
International Transactions on Electrical Energy Systems (2018) Vol. 29, Iss. 1, pp. e2698-e2698
Open Access | Times Cited: 23
A Deep Learning Model for Fault Diagnosis with a Deep Neural Network and Feature Fusion on Multi-Channel Sensory Signals
Qing Ye, Shaohu Liu, Changhua Liu
Sensors (2020) Vol. 20, Iss. 15, pp. 4300-4300
Open Access | Times Cited: 18
Sliding Mode Observer-Based Fault Detection and Isolation Approach for a Wind Turbine Benchmark
Vicente Borja-Jaimes, Manuel Adam‐Medina, B. López-Zapata, et al.
Processes (2021) Vol. 10, Iss. 1, pp. 54-54
Open Access | Times Cited: 13
Improvement of Fast Kurtogram Combined with PCA for Multiple Weak Fault Features Extraction
Yongxing Song, Jingting Liu, Linhua Zhang, et al.
Processes (2020) Vol. 8, Iss. 9, pp. 1059-1059
Open Access | Times Cited: 13
Air leaks fault detection in maintenance using machine learning
Neveen Barakat, Liana Hajeir, Sarah Alattal, et al.
Journal of Quality in Maintenance Engineering (2024) Vol. 30, Iss. 2, pp. 391-408
Closed Access | Times Cited: 1
Fault Detection of Rotating Machines Using poly-Coherent Composite Spectrum of Measured Vibration Responses with Machine Learning
Khalid M. Almutairi, Jyoti K. Sinha, Haobin Wen
Machines (2024) Vol. 12, Iss. 8, pp. 573-573
Open Access | Times Cited: 1
Tackling Industrial Downtimes with Artificial Intelligence in Data-Driven Maintenance
Marcel Hoffmann, Rainer Lasch
ACM Computing Surveys (2023) Vol. 56, Iss. 4, pp. 1-33
Closed Access | Times Cited: 4
Risk-Informed Support Vector Machine Regression Model for Component Replacement—A Case Study of Railway Flange Lubricator
Frederick Appoh, Akilu Yunusa‐Kaltungo
IEEE Access (2021) Vol. 9, pp. 85418-85430
Open Access | Times Cited: 8
Model-Free Data Mining of Families of Rotating Machinery
Elizabeth Hofer, Martin v. Mohrenschildt
Applied Sciences (2022) Vol. 12, Iss. 6, pp. 3178-3178
Open Access | Times Cited: 4
Fault Diagnosis in Industries: How to Improve the Health Assessment of Rotating Machinery
Francesca Calabrese, Alberto Regattieri, Marco Bortolini, et al.
Smart innovation, systems and technologies (2021), pp. 257-266
Closed Access | Times Cited: 3
Evaluation of the Dynamic Behavior of a Rotor Based on a Vibration Diagnosis
Mohammed Bouaicha, Imad El Adraoui, Hassan Gziri, et al.
Lecture notes in networks and systems (2022), pp. 757-766
Closed Access | Times Cited: 1
Automated Faults Diagnosis Framework for Rotating Machines Under Combined Faults Scenarios
Ruifeng Cao, Akilu Yunusa‐Kaltungo
(2023), pp. 1-8
Closed Access
Advanced Methods in Rotating Machines
Xiaohua Song, Jing Liu, Chaobo Chen, et al.
Energies (2022) Vol. 15, Iss. 15, pp. 5414-5414
Open Access
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