Vibration and acoustic emission ae based tool condition classification in high speed machining hsm of titanium alloy ti 6al 4v using machine learning algorithms

dc.contributor.guide	Ramachandran, K I
dc.coverage.spatial	Mechanical Engineering
dc.creator.researcher	Prishnakumar, P
dc.date.accessioned	2017-05-12T04:43:31Z
dc.date.available	2017-05-12T04:43:31Z
dc.date.awarded	n.d.
dc.date.completed	2017
dc.date.registered	n.d.
dc.description.abstract	Appendix available
dc.description.note	Appendix p. 192-196, Bibliography 197-207
dc.format.accompanyingmaterial	None
dc.format.dimensions	-
dc.format.extent	207 p.
dc.identifier.uri	http://hdl.handle.net/10603/149055
dc.language	English
dc.publisher.institution	Dept. of Mechanical Engineering
dc.publisher.place	Coimbatore
dc.publisher.university	Amrita Vishwa Vidyapeetham (University)
dc.relation	-
dc.rights	university
dc.source.inflibnet	INFLIBNET
dc.subject.keyword	Acoustic
dc.subject.keyword	Classification
dc.subject.keyword	Condition
dc.subject.keyword	Vibration
dc.title	Vibration and acoustic emission ae based tool condition classification in high speed machining hsm of titanium alloy ti 6al 4v using machine learning algorithms
dc.title.alternative	-
dc.type.degree	Ph.D.