An Application of Wavelet Analysis to Assess Partial Discharge Evolution by Acoustic Emission Sensor

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Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidad Técnica Federico Santa María-
Autor(es): dc.creatorSantos, Vitor Vecina dos-
Autor(es): dc.creatorCastro, Bruno Albuquerque de-
Autor(es): dc.creatorBinotto, Amanda-
Autor(es): dc.creatorRey, Jorge Alfredo Ardila-
Autor(es): dc.creatorLucas, Guilherme Beraldi-
Autor(es): dc.creatorAndreoli, André Luiz-
Data de aceite: dc.date.accessioned2025-08-21T21:29:28Z-
Data de disponibilização: dc.date.available2025-08-21T21:29:28Z-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2019-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.3390/ecsa-7-08244-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/247575-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/247575-
Descrição: dc.descriptionUnder normal operation, insulation systems of high voltage electrical devices, like power transformers, are constantly subjected to multiple types of stresses (electrical, thermal, mechanical, environmental, etc.), which can lead to a degradation of the machine insulation. One of the main indicators of the dielectric degradation process is the presence of partial discharges (PD). Although it starts due to operational stresses, PD can cause a progressive insulation deterioration, since it is characterized by localized current pulses that emit heat, UV radiation, acoustic, and electromagnetic waves. In this sense, acoustic emission (AE) transducers are wildly applied in PD detection. The goal is to reduce maintenance costs by predictive actions and avoid total failures. Becasue of the progressive deterioration, the assessment of the PD evolution is crucial for improving the maintenance planning and ensure the operation of the transformer. Based on this issue, this article presents a new wavelet -based analysis in order to characterize the PD evolution. Three levels of failures were carried out in a transformer and the acoustic signals captured by a lead zirconate titanate piezoelectric transducer were processed by discrete wavelet transform. The experimental results revealed that the energy of the approximation levels increasing with the failure evolution. More specifically, levels 4, 6, 7, and 10 presented a linear fit to characterize the phenomena, enhancing the applicability of the proposed approach to transformer monitoring.-
Descrição: dc.descriptionSão Paulo State University (UNESP) School of Engineering Bauru Department of Electrical Engineering, SP-
Descrição: dc.descriptionIEEE Women in Engineering São Paulo State University (UNESP), SP-
Descrição: dc.descriptionDepartment of Electrical Engineering Universidad Técnica Federico Santa María, Av. Vicuña Mackenna 3939-
Descrição: dc.descriptionSão Paulo State University (UNESP) School of Engineering Bauru Department of Electrical Engineering, SP-
Descrição: dc.descriptionIEEE Women in Engineering São Paulo State University (UNESP), SP-
Idioma: dc.languageen-
Relação: dc.relationEngineering Proceedings-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectnon-destructive methods-
Palavras-chave: dc.subjectpartial discharge evolution-
Palavras-chave: dc.subjectpiezoelectric sensors-
Palavras-chave: dc.subjectwavelet trasform-
Título: dc.titleAn Application of Wavelet Analysis to Assess Partial Discharge Evolution by Acoustic Emission Sensor-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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