Correspondence between intrinsic mode functions and slow flows

Lee, YS; Tsakirtzis, S; Vakakis, AF; Bergman, LA; McFarland, DM

dc.contributor.author	Lee, YS	en
dc.contributor.author	Tsakirtzis, S	en
dc.contributor.author	Vakakis, AF	en
dc.contributor.author	Bergman, LA	en
dc.contributor.author	McFarland, DM	en
dc.date.accessioned	2014-03-01T02:52:38Z
dc.date.available	2014-03-01T02:52:38Z
dc.date.issued	2010	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35965
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-77953750776&partnerID=40&md5=c01894cd760ac3f43ae9afe1a1a905c3	en
dc.subject.other	Analyticity	en
dc.subject.other	Coupled oscillators	en
dc.subject.other	Empirical mode decomposition	en
dc.subject.other	Flow analysis	en
dc.subject.other	Flow model	en
dc.subject.other	Intrinsic mode functions	en
dc.subject.other	Mathematical expressions	en
dc.subject.other	Non-linear system identification	en
dc.subject.other	Non-parametric	en
dc.subject.other	Oscillatory mode	en
dc.subject.other	Physical systems	en
dc.subject.other	Physics-based	en
dc.subject.other	Slow flow	en
dc.subject.other	Strongly nonlinear	en
dc.subject.other	Structural systems	en
dc.subject.other	Theoretical foundations	en
dc.subject.other	Time domain	en
dc.subject.other	Two-degree-of-freedom	en
dc.subject.other	Decomposition	en
dc.subject.other	Oscillators (electronic)	en
dc.subject.other	Signal analysis	en
dc.subject.other	Structures (built objects)	en
dc.subject.other	Time series	en
dc.subject.other	Time domain analysis	en
dc.title	Correspondence between intrinsic mode functions and slow flows	en
heal.type	conferenceItem	en
heal.publicationDate	2010	en
heal.abstract	We study the correspondence between analytical and empirical slow-flow analyses, which will form a basis for a time-domain nonparametric nonlinear system identification method. Given a sufficiently dense set of sensors, measured time series recorded throughout a mechanical or structural system contains all information regarding the dynamics of that system. Empirical mode decomposition (EMD) is a useful tool for decomposing the measured time series in terms of intrinsic mode functions (IMFs), which are oscillatory modes embedded in the data that fully reproduce the time series. The equivalence of responses of the analytical slow-flow models and the dominant IMFs derived from EMD provides a physics-based theoretical foundation for EMD, which currently is performed formally, in an ad hoc fashion. First deriving appropriate mathematical expressions governing the empirical slow flows and based on analyticity conditions, we demonstrate only close correspondence between analytical and empirical slow flows in a physical system that can be modeled as a two-degree-of-freedom strongly nonlinear coupled oscillators. Copyright © 2009 by ASME.	en
heal.journalName	Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference 2009, DETC2009	en
dc.identifier.volume	1	en
dc.identifier.issue	PART A	en
dc.identifier.spage	661	en
dc.identifier.epage	670	en