Estimation of nonlinearities from pseudodynamic and dynamic responses of bridge structures using the Delay Vector Variance method

被引:5
|
作者
Jaksic, Vesna [1 ]
Mandic, Danilo P. [2 ]
Karoumi, Raid [3 ]
Basu, Bidroha [1 ,4 ]
Pakrashi, Vikram [1 ]
机构
[1] Natl Univ Ireland Univ Coll Cork, Sch Engn, Dynam Syst & Risk Lab, Civil & Environm Engn, Cork, Ireland
[2] Univ London Imperial Coll Sci Technol & Med, Dept Elect & Elect Engn, Commun & Signal Proc Res Grp, London, England
[3] Royal Inst Technol KTH Stockholm, Civil & Architectural Engn, Stockholm, Sweden
[4] Indian Inst Sci, Dept Civil Engn, Bangalore 560012, Karnataka, India
基金
爱尔兰科学基金会;
关键词
Delay Vector Variance (DVV); Signal nonlinearity; System identification; Instrumentation; Condition monitoring; Bridge; VIBRATING STRUCTURES; AMBIENT VIBRATION; DAMAGE DETECTION; IDENTIFICATION; FREQUENCY; CALIBRATION; KURTOSIS; OUTPUT; SYSTEMS; SERIES;
D O I
10.1016/j.physa.2015.08.026
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Analysis 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. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:100 / 120
页数:21
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