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Diagnosis of broken bar fault in three-phase induction motors using fibre bragg grating strain sensors assisted by an algorithm

2025Comunicação em conferência Acesso aberto
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datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.fosEngenharia e Tecnologia::Engenharia Mecânica
datacite.subject.sdg04:Educação de Qualidade
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
dc.contributor.authorCavalcanti, Rafael
dc.contributor.authorDreyer, Uilian José
dc.contributor.authorAguiar, Everton Luiz de
dc.contributor.authorSilva, Jean Carlos Cardozo da
dc.contributor.authorSousa, Kleiton Morais
dc.contributor.authorMendes, Andre C.
dc.date.accessioned2026-06-12T11:06:41Z
dc.date.available2026-06-12T11:06:41Z
dc.date.issued2025
dc.description.abstractThis study developed an algorithm running on the cloud that makes data process and diagnoses broken rotor bar faults in three-phase induction motors (TIMs), by analyzing stator dynamic deformation using fibre Bragg gratings (FBGs) as sensors. This method can diagnose mechanical faults (misalignment, imbalance) and electrical faults (fractures or cracks in rotor rings or bars). FBG-based sensors were used due to their high multiplexing capability, electromagnetic radiation immunity, and long-distance operation. Tests were conducted on a small-scale induction motor (3 HP) coupled to a generator to simulate load and the generator supplied by the grid. Were used 1 healthy rotor and one rotor with a broken bar fault running at two load conditions, 75% and 100%. The algorithm successfully identified broken bar faults in two frequency regions: around the mechanical rotational frequency of the rotor 28.06 Hz and 31.014 Hz operating at 75%; 25.325 Hz and 32.995 Hz operating at 100% and approximately twice the electrical frequency supply, 118.455 Hz and 123.942 Hz operating at 75%; 117.237 Hz and 124.683 Hz operating at 100%. The system showed high sensitivity, a good signal-to-noise ratio, and advantages over conventional methods for detecting broken bar faults in induction motors.eng
dc.description.sponsorshipThe authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021) and the Multi-User Photonics Facility—Federal University of Technology – Paraná, Curitiba (UTFPR - CT). This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001”, of Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), from Fundação Araucária (FA) and from Financiadora de Estudos e Projetos (FINEP).
dc.identifier.citationCavalcanti, Rafael; Dreyer, Uilian José; Aguiar, Everton Luiz de; Silva, Jean Carlos Cardozo da; Sousa, Kleiton Morais; Mendes, André (2025). Diagnosis of broken bar fault in three-phase induction motors using fibre bragg grating strain sensors assisted by an algorithm. In 2025 International Microwave and Optoelectronics Conference-IMOC. p. 451-455. ISBN 979-8-3503-9275-3/25. DOI: 10.1109/imoc65414.2025.11365738
dc.identifier.doi10.1109/imoc65414.2025.11365738
dc.identifier.isbn979-8-3503-9275-3/25
dc.identifier.urihttp://hdl.handle.net/10198/36864
dc.language.isoeng
dc.peerreviewedyes
dc.publisherInstitute of Electrical and Electronics Engineers
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relation.ispartof2025 SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference (IMOC)
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAlgorithm
dc.subjectDynamic strain
dc.subjectFiber Bragg gratings
dc.subjectInduction motor
dc.subjectRotor broken bar fault
dc.titleDiagnosis of broken bar fault in three-phase induction motors using fibre bragg grating strain sensors assisted by an algorithmeng
dc.typeconference paper
dspace.entity.typePublication
oaire.awardNumberUIDB/05757/2020
oaire.awardNumberUIDP/05757/2020
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT
oaire.citation.endPage455
oaire.citation.startPage451
oaire.citation.title2025 International Microwave and Optoelectronics Conference-IMOC
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameMendes
person.givenNameAndre C.
person.identifier.ciencia-id6718-7AE9-0953
person.identifier.orcid0000-0001-6390-1250
person.identifier.scopus-author-id54920397900
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
relation.isAuthorOfPublication469e664f-f0ce-4ccf-a00d-21c086996765
relation.isAuthorOfPublication.latestForDiscovery469e664f-f0ce-4ccf-a00d-21c086996765
relation.isProjectOfPublication6e01ddc8-6a82-4131-bca6-84789fa234bd
relation.isProjectOfPublicationd0a17270-80a8-4985-9644-a04c2a9f2dff
relation.isProjectOfPublication.latestForDiscovery6e01ddc8-6a82-4131-bca6-84789fa234bd

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