Ensemble Subspace Discriminant Classifiers for Misalignment Fault Classification Using Vibro-acoustic Sensor Data Fusion

Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/11942

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DC Field	Value	Language
dc.contributor.author	Jalan, Arun Kumar	-
dc.date.accessioned	2023-09-18T06:45:11Z	-
dc.date.available	2023-09-18T06:45:11Z	-
dc.date.issued	2022-05	-
dc.identifier.uri	https://link.springer.com/article/10.1007/s42417-022-00548-2	-
dc.identifier.uri	http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/11942	-
dc.description.abstract	Misalignment is one of the major reasons for rotating machinery breakdown. Conventionally, misalignment diagnosis is done by the occurrence of a strong peak at 2x running speed is widely accepted.	en_US
dc.language.iso	en	en_US
dc.publisher	Springer	en_US
dc.subject	Mechanical Engineering	en_US
dc.subject	Vibro-Acoustic Sensor	en_US
dc.subject	Data Fusion	en_US
dc.title	Ensemble Subspace Discriminant Classifiers for Misalignment Fault Classification Using Vibro-acoustic Sensor Data Fusion	en_US
dc.type	Article	en_US
Appears in Collections:	Department of Mechanical engineering

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