Jaksic, VesnaVesnaJaksicMandic, Danilo P.Danilo P.MandicKaroumi, RaidRaidKaroumiBasu, BiswajitBiswajitBasuPakrashi, VikramVikramPakrashi2019-05-142019-05-142015 Elsev2016-01-01Physica A: Statistical Mechanics and its Applications0378-4371http://hdl.handle.net/10197/10435Analysis of the variability in the responses of large structural systems and quantification of their linearity or nonlinearity as a potential non-invasive means of structural system assessment from output-only condition remains a challenging problem. In this study, the Delay Vector Variance (DVV) method is used for full scale testing of both pseudo-dynamic and dynamic responses of two bridges, in order to study the degree of nonlinearity of their measured response signals. The DVV detects the presence of determinism and nonlinearity in a time series and is based upon the examination of local predictability of a signal. The pseudo-dynamic data is obtained from a concrete bridge during repair while the dynamic data is obtained from a steel railway bridge traversed by a train. We show that DVV is promising as a marker in establishing the degree to which a change in the signal nonlinearity reflects the change in the real behaviour of a structure. It is also useful in establishing the sensitivity of instruments or sensors deployed to monitor such changes.enThis is the author’s version of a work that was accepted for publication in Physica A: Statistical Mechanics and its Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Physica A: Statistical Mechanics and its Applications (441, (2016))Delay Vector Variance (DVV)Signal nonlinearitySystem identificationInstrumentationCondition monitoringBridgeEstimation of nonlinearities from pseudodynamic and dynamic responses of bridge structures using the Delay Vector Variance methodJournal Article44110012010.1016/j.physa.2015.08.0262019-05-05R1357012/ISCA/2493https://creativecommons.org/licenses/by-nc-nd/3.0/ie/