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Fault diagnosis for wind turbine gearboxes by using deep enhanced fusion network

dc.contributor.authorPu, Ziqiang
dc.contributor.authorLi, Chuan
dc.contributor.authorZhang, Shaohui
dc.contributor.authorBai, Yun
dc.date.accessioned2021-09-08T10:58:15Z
dc.date.available2021-09-08T10:58:15Z
dc.date.issued2021
dc.description.abstractThe gearbox will directly affect the safety and reliability of the wind turbine, whose failure leads to low processing accuracy and certain economic losses. To address this issue, a deep enhanced fusion network (DEFN) is proposed for the fault diagnosis of the wind turbine gearbox with the experimental vibration data. In the proposed DEFN, three sparse autoencoders are first applied to extract deep features of three-axial vibration signals, respectively. Second, a feature enhancement mapping is developed to minimize the intraclass distance of the deep features in the three-axial vibration. Finally, the fused three-axis features are put into an echo state network for fault classification. The results of the experiment carried out in a wind turbine show that the proposed DEFN has a good fault diagnosis accuracy compared with other peer models.
dc.description.sponsorshipNational Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [51775112, 71801044, 51975121]; Guangdong Research Foundation [2019B1515120095]; Chongqing Natural Science Fund [cstc2019jcyjzdxmX0013]; CTBU Project [KFJJ2019060]
dc.description.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.doi10.1109/TIM.2020.3024048
dc.identifier.issn0018-9456
dc.identifier.urihttp://hdl.handle.net/10400.1/17074
dc.language.isoeng
dc.peerreviewedyes
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.subjectEcho state network (ESN)
dc.subjectFault diagnosis
dc.subjectFeature enhancement
dc.subjectSparse autoencoder (SAE)
dc.subjectWind turbine gearbox
dc.subject.otherEngineering; Instruments & Instrumentation
dc.titleFault diagnosis for wind turbine gearboxes by using deep enhanced fusion network
dc.typejournal article
dspace.entity.typePublication
oaire.citation.startPage2501811
oaire.citation.titleIeee Transactions on Instrumentation and Measurement
oaire.citation.volume70
person.familyNamePu
person.familyNameBai
person.givenNameZiqiang
person.givenNameYun
person.identifier.orcid0000-0001-8186-8239
person.identifier.orcid0000-0003-2710-7994
person.identifier.scopus-author-id55461096500
rcaap.rightsrestrictedAccess
rcaap.typearticle
relation.isAuthorOfPublication34dba8e4-de5d-4df1-86cd-9e8d5252c255
relation.isAuthorOfPublication395ae945-8e87-47b3-9edf-6fa1f380097f
relation.isAuthorOfPublication.latestForDiscovery34dba8e4-de5d-4df1-86cd-9e8d5252c255

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