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Matos-Carvalho, J., Stefenon, S., Yow, K., García Ovejero, R. & Leithardt, V. (2025). N-BEATS neural network applied for insulator fault prediction considering EMD methods. 5th International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2025. IEEE. https://doi.org/10.1109/ICECCME64568.2025.11277686

M. J. P. et al.,  "N-BEATS neural network applied for insulator fault prediction considering EMD methods", in 5th Int. Conf. on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2025, Zanzibar, Tanzania, United Republic of, IEEE, 2025

@inproceedings{p.2025_1790104499021,
	author = "Matos-Carvalho, J. and Stefenon, S. and Yow, K. and García Ovejero, R. and Leithardt, V.",
	title = "N-BEATS neural network applied for insulator fault prediction considering EMD methods",
	booktitle = "5th International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2025",
	year = "2025",
	editor = "",
	volume = "",
	number = "",
	series = "",
	doi = "10.1109/ICECCME64568.2025.11277686",
	publisher = "IEEE",
	address = "Zanzibar, Tanzania, United Republic of",
	organization = "",
	url = "https://ieeexplore.ieee.org/document/11277686"
}

TY  - CPAPER
TI  - N-BEATS neural network applied for insulator fault prediction considering EMD methods
T2  - 5th International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2025
AU  - Matos-Carvalho, J.
AU  - Stefenon, S.
AU  - Yow, K.
AU  - García Ovejero, R.
AU  - Leithardt, V.
PY  - 2025
DO  - 10.1109/ICECCME64568.2025.11277686
CY  - Zanzibar, Tanzania, United Republic of
UR  - https://ieeexplore.ieee.org/document/11277686
AB  - The electrical distribution system relies on the qual-ity of insulation to ensure the power supply. When an insulator has a high level of surface contamination, the leakage current increases, leading to a disruptive discharge. To mitigate this problem, one solution is to evaluate the leakage current in relation to the insulator's contamination, as presented in the IEC 60507 standard. To improve the ability to predict faults in insulators, this paper proposes using the neural basis expansion analysis for time series forecasting (N-BEATS) to predict faults in the power grid. For signal denoising, the empirical mode decomposition (EMD) methods are applied. The model proposed in this paper has an input filter stage ensuring that only the trend in leakage current variation is evaluated. The proposed method shows promise, being superior to other deep learning models. 
ER  -