Published September 28, 2023
| Version 1.0.0
Dataset
Open
MATLAB codes for : "Diagnosis and Prognosis of Faults in High-Speed Aeronautical Bearings with a Collaborative Selection Incremental Deep Transfer Learning Approach".
Creators
- 1. Laboratory of Automation and Manufacturing Engineering, University of Batna 2, Batna 05000, Algeria
Contributors
Contact person:
- 1. Laboratory of automation and manufacturing Engineering, University of Batna 2, 0 Btana 5000, Algeria
Description
The package contains all the materials needed to reproduce the findings of our paper. The paper is published by MDPI Applied Sciences journal and its details are as follow.
Berghout, T.; Benbouzid, M. Diagnosis and Prognosis of Faults in High-Speed Aeronautical Bearings with a Collaborative Selection Incremental Deep Transfer Learning Approach. Appl. Sci. 2023, 13, 10916. https://doi.org/10.3390/app131910916
1) Please you need to download the dataset from original link provided by introductory paper (Please read the above paper to find out about the datset used).
2) Put the data in folders "RawData" for both experments.
3) Please run the files for each experiment as provided, in alphabetical order.
Files
Matlab_codes_open_source.zip
Files
(41.9 kB)
| Name | Size | Download all |
|---|---|---|
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md5:c3357eab7de9e82fabd298a2ac026118
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41.9 kB | Preview Download |
Additional details
Related works
- Is supplement to
- Journal article: 10.3390/app131910916 (DOI)
References
- Berghout, T.; Benbouzid, M. Diagnosis and Prognosis of Faults in High-Speed Aeronautical Bearings with a Collaborative Selection Incremental Deep Transfer Learning Approach. Appl. Sci. 2023, 13, 10916. https://doi.org/10.3390/app131910916