Logo do repositório
 
Publicação

Fault Prediction Based on Leakage Current in Contaminated Insulators Using Enhanced Time Series Forecasting Models

2022-08-16Artigo científico Desconhecido
Ver registo simples
dc.contributor.authorNemesio Fava Sopelsa NetoPT
dc.contributor.authorFrizzo Stefenon, Stéfano
dc.contributor.authorMeyer, Luiz Henrique
dc.contributor.authorRAUL, GARCIA
dc.contributor.authorLEITHARDT, VALDERI
dc.date.accessioned2023-02-01T18:24:19ZPT
dc.date.available2023-02-01T18:24:19ZPT
dc.date.issued2022-08-16PT
dc.date.updated2022-08-25T22:46:03Z
dc.description.abstractTo improve the monitoring of the electrical power grid, it is necessary to evaluate the influence of contamination in relation to leakage current and its progression to a disruptive discharge. In this paper, insulators were tested in a saline chamber to simulate the increase of salt contamination on their surface. From the time series forecasting of the leakage current, it is possible to evaluate the development of the fault before a flashover occurs. In this paper, for a complete evaluation, the long short-term memory (LSTM), group method of data handling (GMDH), adaptive neuro-fuzzy inference system (ANFIS), bootstrap aggregation (bagging), sequential learning (boosting), random subspace, and stacked generalization (stacking) ensemble learning models are analyzed. From the results of the best structure of the models, the hyperparameters are evaluated and the wavelet transform is used to obtain an enhanced model. The contribution of this paper is related to the improvement of well-established models using the wavelet transform, thus obtaining hybrid models that can be used for several applications. The results showed that using the wavelet transform leads to an improvement in all the used models, especially the wavelet ANFIS model, which had a mean RMSE of 1.58 × 10−3, being the model that had the best result. Furthermore, the results for the standard deviation were 2.18 × 10−19, showing that the model is stable and robust for the application under study. Future work can be performed using other components of the distribution power grid susceptible to contamination because they are installed outdoors.pt_PT
dc.description.versionN/Apt_PT
dc.identifier.doi10.3390/s22166121pt_PT
dc.identifier.slugcv-prod-3036346
dc.identifier.urihttp://hdl.handle.net/10400.26/43556PT
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectLSTM;pt_PT
dc.subjectGMDH;pt_PT
dc.subjectANFIS;pt_PT
dc.subjectensemble learning models;pt_PT
dc.subjectwavelet;pt_PT
dc.subjecttime series forecastingpt_PT
dc.titleFault Prediction Based on Leakage Current in Contaminated Insulators Using Enhanced Time Series Forecasting Modelspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleSensorspt_PT
person.familyNameStefenon
person.familyNameMeyer
person.familyNameRAUL
person.familyNameREIS QUIETINHO LEITHARDT
person.givenNameStefano Frizzo
person.givenNameLuiz Henrique
person.givenNameGARCIA
person.givenNameVALDERI
person.identifier916543
person.identifierJsOq45sAAAAJ&hl=pt-PT
person.identifier.ciencia-id4019-BB36-7F74
person.identifier.ciencia-id0614-5834-E7F3
person.identifier.orcid0000-0002-3723-616X
person.identifier.orcid0000-0002-4849-4041
person.identifier.orcid0000-0001-8781-6392
person.identifier.orcid0000-0003-0446-9271
person.identifier.ridAAD-7639-2019
person.identifier.scopus-author-id57194147390
person.identifier.scopus-author-id35303109600
rcaap.cv.cienciaid0614-5834-E7F3 | Valderi Reis Quietinho Leithardt
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationae8b0861-1e25-47fb-bcdb-a44c98768634
relation.isAuthorOfPublication2bfe65fe-0603-4716-b962-0927333a87e5
relation.isAuthorOfPublicationb201a693-6a6e-4cf7-a8f0-c40d3494d244
relation.isAuthorOfPublicationab15f7c6-e882-406e-813d-2629e9cec5c8
relation.isAuthorOfPublication.latestForDiscovery2bfe65fe-0603-4716-b962-0927333a87e5

Ficheiros

Coleções

VALORIZA - Artigos em Revistas Científicas
Carregar mais