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Artificial Neural Networks applied in the predictive maintenance of Electricity Generating Units through the Partial Discharges Classification
Artificial Neural Networks applied in the predictive maintenance of Electricity Generating Units through the Partial Discharges Classification
Cardoso, Regis; Marchesini, Giancarlo; Santos Junior, Elço João dos; Furlani, Alisson Lopes
Full Article:
"Electrical equipment in transmission lines and power distribution oftenexperiences faults due to insulation failures. Studies have shown that insulation defectscause localized electrical discharges, known as Partial Discharges (PD). PD analysisis an effective method for monitoring electrical equipment. Repeated PDs weaken theinsulation and may eventually cause system failure. Regulations identify seven typesof PDs, each linked to specific insulation failures and criticality levels. This articlepresents promising results using Artificial Intelligence algorithms, specifically ArtificialNeural Networks, to classify PD types with over 99% accuracy. The algorithm operatesas a microservice, automatically handling search, classification, and event generation."
"Electrical equipment in transmission lines and power distribution oftenexperiences faults due to insulation failures. Studies have shown that insulation defectscause localized electrical discharges, known as Partial Discharges (PD). PD analysisis an effective method for monitoring electrical equipment. Repeated PDs weaken theinsulation and may eventually cause system failure. Regulations identify seven typesof PDs, each linked to specific insulation failures and criticality levels. This articlepresents promising results using Artificial Intelligence algorithms, specifically ArtificialNeural Networks, to classify PD types with over 99% accuracy. The algorithm operatesas a microservice, automatically handling search, classification, and event generation."
Palavras-chave: - -
DOI: 10.5151/siintec2024-393169
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Como citar:
Cardoso, Regis; Marchesini, Giancarlo; Santos Junior, Elço João dos; Furlani, Alisson Lopes; "Artificial Neural Networks applied in the predictive maintenance of Electricity Generating Units through the Partial Discharges Classification", p-520-537.
In: .
São Paulo: Blucher,
2024.
ISSN 23577592,
DOI 10.5151/siintec2024-393169
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TY - CONF T1 - Artificial Neural Networks applied in the predictive maintenance of Electricity Generating Units through the Partial Discharges Classification JO - Blucher Engineering Proceedings VL - 11 IS - 2 SP - 520 EP - 537 PY - 2024 T2 - X Simpósio Internacional de Inovação e Tecnologia AU - , , , SN - 23577592 DO - http://dx.doi.org/10.5151/siintec2024-393169 UR - www.proceedings.blucher.com.br/article-details/artificial-neural-networks-applied-in-the-predictive-maintenance-of-electricity-generating-units-through-the-partial-discharges-classification-39881 KW - None ER -
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@article{Cardoso20144,
title="Artificial Neural Networks applied in the predictive maintenance of Electricity Generating Units through the Partial Discharges Classification",
journal="Blucher Engineering Proceedings",
volume="11",
number="2",
pages="520 - 537",
year="2024",
note="",
issn="23577592",
doi="http://dx.doi.org/10.5151/siintec2024-393169",
url="www.proceedings.blucher.com.br/article-details/artificial-neural-networks-applied-in-the-predictive-maintenance-of-electricity-generating-units-through-the-partial-discharges-classification-39881",
author="Regis Cardoso", "Giancarlo Marchesini", "Elço João dos Santos Junior", "Alisson Lopes Furlani",
keywords="None",
}
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Regis Cardoso, Giancarlo Marchesini, Elço João dos Santos Junior, Alisson Lopes Furlani, Artificial Neural Networks applied in the predictive maintenance of Electricity Generating Units through the Partial Discharges Classification, Blucher Engineering Proceedings, Volume 11, 2024, Pages 520-537, ISSN 23577592, http://dx.doi.org/10.5151/siintec2024-393169 (www.proceedings.blucher.com.br/article-details/artificial-neural-networks-applied-in-the-predictive-maintenance-of-electricity-generating-units-through-the-partial-discharges-classification-39881) Palavras-chave:: None;