MATLAB Codes for: Fault Diagnosis in Drones via Multiverse Augmented Extreme Recurrent Expansion of Acoustic Emissions with Uncertainty Bayesian Optimisation
Description
The following MATLAB codes belong to the paper following paper which has been publication in MDPI Machines. This repository includes all the necessary MATLAB scripts and functions used in the research for diagnosing faults in drones using advanced acoustic emission analysis and optimization techniques. The dataset used in this paper is referenced in the article. Please check the publication for the dataset reference. Download the dataset, decompress it, and place it in the same repository as these codes to ensure proper functionality. For any queries or further information, please refer to this paper.
Berghout, Tarek, and Mohamed Benbouzid. 2024. "Fault Diagnosis in Drones via Multiverse Augmented Extreme Recurrent Expansion of Acoustic Emissions with Uncertainty Bayesian Optimisation" Machines 12, no. 8: 504. https://doi.org/10.3390/machines12080504
Files
Zenodo.zip
Files
(6.9 MB)
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Additional details
References
- Berghout, Tarek, and Mohamed Benbouzid. 2024. "Fault Diagnosis in Drones via Multiverse Augmented Extreme Recurrent Expansion of Acoustic Emissions with Uncertainty Bayesian Optimisation" Machines 12, no. 8: 504. https://doi.org/10.3390/machines12080504