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dc.contributor.advisorWang, Kesheng
dc.contributor.advisorStrandhagen, Jan Ola
dc.contributor.advisorHe, Yafei
dc.contributor.authorLi, Zhe
dc.date.accessioned2018-06-04T12:50:27Z
dc.date.available2018-06-04T12:50:27Z
dc.date.issued2018
dc.identifier.isbn978-82-326-3055-4
dc.identifier.issn1503-8181
dc.identifier.urihttp://hdl.handle.net/11250/2500192
dc.language.isoengnb_NO
dc.publisherNTNUnb_NO
dc.relation.ispartofseriesDoctoral theses at NTNU;2018:132
dc.titleDeep Learning Driven Approaches for Predictive Maintenance: A Framework of Intelligent Fault Diagnosis and Prognosis in the Industry 4.0 Eranb_NO
dc.typeDoctoral thesisnb_NO
dc.subject.nsiVDP::Technology: 500::Mechanical engineering: 570nb_NO


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