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Influence of Blade Pass Frequency Vibrations on MCSA-Based Rotor Fault Detection of Induction Motors

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dc.contributor.authorPark, Yonghyun-
dc.contributor.authorJeong, Myung-
dc.contributor.authorLee, Sang Bin-
dc.contributor.authorAlfonso Antonino-Daviu, Jose-
dc.contributor.authorTeska, Mike-
dc.date.accessioned2021-09-03T06:32:07Z-
dc.date.available2021-09-03T06:32:07Z-
dc.date.created2021-06-16-
dc.date.issued2017-05-
dc.identifier.issn0093-9994-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/83536-
dc.description.abstractMotor current signature analysis (MCSA) has recently become widespread in industry for on-line detection of rotor cage faults in induction motors for preventing forced outages. Although it can provide low cost remote monitoring of rotor faults, cases of false indications have been reported, where the causes of some false indications are still unknown. It is shown for the first time in this work that high-amplitude blade pass frequency (BPF) vibrations produced in pumps, fans, or compressors can cause false rotor fault indications if the number of motor poles is an integer multiple of the number of blades. The influence of BPF vibration on MCSA-based rotor fault detection is analyzed, and it is shown that the interaction between BPF vibration and rotor faults can produce false positive and negative fault indications. Alternative test methods capable of separating the influence of the BPF vibration and rotor faults are suggested for avoiding false MCSA alarms. The claims made in the paper are verified experimentally on a custom-built 380 V induction motor-centrifugal pump system setup.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.subjectCURRENT SIGNATURE ANALYSIS-
dc.subjectDIAGNOSIS-
dc.subjectOSCILLATIONS-
dc.subjectMACHINES-
dc.subjectBARS-
dc.titleInfluence of Blade Pass Frequency Vibrations on MCSA-Based Rotor Fault Detection of Induction Motors-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, Sang Bin-
dc.identifier.doi10.1109/TIA.2017.2672526-
dc.identifier.scopusid2-s2.0-85028058779-
dc.identifier.wosid000402062600034-
dc.identifier.bibliographicCitationIEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, v.53, no.3, pp.2049 - 2058-
dc.relation.isPartOfIEEE TRANSACTIONS ON INDUSTRY APPLICATIONS-
dc.citation.titleIEEE TRANSACTIONS ON INDUSTRY APPLICATIONS-
dc.citation.volume53-
dc.citation.number3-
dc.citation.startPage2049-
dc.citation.endPage2058-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryEngineering, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.subject.keywordPlusCURRENT SIGNATURE ANALYSIS-
dc.subject.keywordPlusDIAGNOSIS-
dc.subject.keywordPlusOSCILLATIONS-
dc.subject.keywordPlusMACHINES-
dc.subject.keywordPlusBARS-
dc.subject.keywordAuthorCondition monitoring-
dc.subject.keywordAuthordiagnostics-
dc.subject.keywordAuthorinduction motor-
dc.subject.keywordAuthorspectral analysis-
dc.subject.keywordAuthorsymmetrical components-
dc.subject.keywordAuthorwavelet transformation-
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