Sensitivity analysis of an information maximization approach to the Blind Separation of the vibration responses of defective rolling element bearings

Yiakopoulos, C; Antoniadis, I

dc.contributor.author	Yiakopoulos, C	en
dc.contributor.author	Antoniadis, I	en
dc.date.accessioned	2014-03-01T02:50:12Z
dc.date.available	2014-03-01T02:50:12Z
dc.date.issued	2005	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34951
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-33144462956&partnerID=40&md5=bfae97dcbf95cc11d349af0e746477c4	en
dc.subject.other	Function evaluation	en
dc.subject.other	Roller bearings	en
dc.subject.other	Rotating machinery	en
dc.subject.other	Sensitivity analysis	en
dc.subject.other	Vibration control	en
dc.subject.other	Rolling element bearings	en
dc.subject.other	Super-Gaussian distributions	en
dc.subject.other	Vibration responses	en
dc.subject.other	Blind source separation	en
dc.title	Sensitivity analysis of an information maximization approach to the Blind Separation of the vibration responses of defective rolling element bearings	en
heal.type	conferenceItem	en
heal.publicationDate	2005	en
heal.abstract	Vibration response of rotating machines is typically mixed and corrupted by a variety of interfering sources and noise, leading to the necessity for the isolation of the useful signal components. A relevant frequently encountered industrial case is the need for the separation of the vibration responses of the same type of bearings inside the same machine. For this purpose, a Blind Source Separation procedure has been successfully applied, based on the maximization of the information transferred in a neural network structure. Thus, a key element for the success of the proposed procedure is the non-linear function used in this single layer Neural Network structure. However, since the vibration response of defective rolling element bearings is characterized by signals with super-Gaussian distributions, a sensitivity analysis of this non-linear function is necessary. First, this analysis is performed in a set of numerical experiments, based on dynamic models of defective bearings. Finally, the same analysis is applied in an experimental test rig. Copyright © 2005 by ASME.	en
heal.journalName	Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference - DETC2005	en
dc.identifier.volume	1 A	en
dc.identifier.spage	643	en
dc.identifier.epage	652	en