Applications of machine learning to machine fault diagnosis: A review and roadmap

Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/20040

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DC Field	Value	Language
dc.contributor.author	Lei, Y	-
dc.contributor.author	Yang, B	-
dc.contributor.author	Jiang, X	-
dc.contributor.author	Jia, F	-
dc.contributor.author	Li, N	-
dc.contributor.author	Nandi, AK	-
dc.date.accessioned	2020-01-20T13:48:10Z	-
dc.date.available	2020-04-01	-
dc.date.available	2020-01-20T13:48:10Z	-
dc.date.issued	2020	-
dc.identifier.citation	Mechanical Systems and Signal Processing, 2020, 138	en_US
dc.identifier.issn	0888-3270	-
dc.identifier.issn	http://dx.doi.org/10.1016/j.ymssp.2019.106587	-
dc.identifier.issn	1096-1216	-
dc.identifier.uri	http://bura.brunel.ac.uk/handle/2438/20040	-
dc.description.sponsorship	National Key R&D Program of China (2018YFB1306100), NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (U1709208), and National Natural Science Foundation of China (61673311).	en_US
dc.language.iso	en	en_US
dc.publisher	Elsevier	en_US
dc.subject	Machines	en_US
dc.subject	Intelligent fault diagnosis	en_US
dc.subject	Machine learning	en_US
dc.subject	Deep learning	en_US
dc.subject	Transfer learning	en_US
dc.title	Applications of machine learning to machine fault diagnosis: A review and roadmap	en_US
dc.type	Article	en_US
dc.identifier.doi	http://dx.doi.org/10.1016/j.ymssp.2019.106587	-
dc.relation.isPartOf	Mechanical Systems and Signal Processing	-
pubs.publication-status	Accepted	-
pubs.volume	138	-
dc.identifier.eissn	1096-1216	-
Appears in Collections:	Dept of Electronic and Electrical Engineering Embargoed Research Papers

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